Apache Spark Jobs in Egypt

Roles & Responsibilities Deliver instructor-led and virtual corporate trainings on Databricks, Microsoft Fabric, Azure Data Engineering, Apache Spark, and related technologies. Facilitate hands-on labs and real-world technical scenarios for enterprise learners. Train professionals on Data Governance tools and concepts including Purview, Collibra, and Lakehouse Architecture. Guide learners through certification preparation and exam readiness. Develop and enhance advanced technical training content for cloud data platforms and analytics technologies. Stay updated with the latest trends in AI-ready data platforms, ETL, Big Data, and Analytics solutions. Travel globally for client training engagements when required. Required Qualifications B. Tech/M. Tech/MCA in Computer Science, IT, Data Science, or related field.5–20 years of experience in Data Engineering, Analytics, or Cloud Data platforms. Microsoft Certified Trainer (MCT) certification is mandatory. Relevant certifications such as Databricks Certified Data Engineer, Microsoft Certified Azure Data Engineer Associate, Snowflake Snow Pro, AWS Data Analytics Specialty, or Google Professional Data Engineer are preferred. Strong expertise in PySpark, Apache Spark, Kafka, Azure Databricks, Power BI, ETL, and modern cloud data platforms. Excellent communication, presentation, and learner engagement skills. Prior experience in corporate training or consulting is highly preferred.<br> Preferred Skills: Data Engineering, Databricks, Azure Data Engineer, PySpark, Apache Spark, Data Governance, Purview, Collibra, Lakehouse Architecture, Microsoft Fabric, Snowflake, Cloud Data Platforms, Power BI, Kafka, Big Data, AI Data Platforms, and Data Analytics.

Valleysoft is a regional IT services provider delivering enterprise technology, application development, process management, and IT support services to clients around the world. Working across the Information Technology and Services sector, the company helps organizations build reliable, scalable digital solutions that support complex business and operational needs.<br><br>This role is an opportunity to contribute to modern data platform initiatives that power analytics and AI use cases across the enterprise. As a Data Engineer - Data Platforms (Databricks), you will play a central role in shaping data infrastructure, supporting cross-functional teams, and helping ensure data systems are performant, secure, and built to scale.<br><br>Responsibilities<br><br>Design, develop, and maintain scalable data pipelines for batch and real-time processing Build and optimize enterprise data platforms using Databricks and Apache Spark Develop ETL/ELT processes to ingest, transform, and integrate data from multiple sources Implement Delta Lake architecture and maintain data lake/lakehouse solutions Collaborate with Data Scientists, AI Engineers, Business Analysts, and application teams to support analytics and AI initiatives Optimize data storage, partitioning, and query performance Develop reusable data engineering frameworks and automation solutions Implement data quality, validation, lineage, and governance processes Ensure data security, privacy, and compliance with enterprise standards Monitor platform performance, troubleshoot production issues, automate deployment and infrastructure, contribute to architecture reviews, and maintain technical documentation and runbooks<br><br>Requirements<br><br>Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field6+ years of data engineering experience working with Databricks and Apache Spark Strong experience with Python and SQL, along with hands-on involvement in ETL/ELT processes Experience working with Delta Lake and cloud platforms Fluent in English Eligibility to work in Egypt

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>Job Overview We are seeking a highly skilled Data Engineering &amp; Warehousing Engineer with 3 11 years of experience to design, develop, and maintain scalable data platforms and enterprise data warehouse solutions. The ideal candidate will have hands-on expertise in building ETL/ELT pipelines, data integration, cloud-based data platforms, and big data processing technologies. You will play a key role in enabling reliable, high-performance analytics and business intelligence solutions. Key Responsibilities Design, develop, and optimize scalable ETL/ELT pipelines for structured and unstructured data. Build and maintain enterprise data warehouses, data lakes, and modern data platforms. Develop real-time and batch data processing solutions. Integrate data from multiple internal and external sources while ensuring data quality and governance. Collaborate with Data Scientists, BI Developers, and business stakeholders to support analytical requirements. Optimize data storage, query performance, and pipeline reliability. Implement data security, monitoring, and governance best practices. Troubleshoot and resolve data pipeline and platform issues. Participate in architecture discussions and contribute to data platform modernization initiatives. Required Technical Skills Cloud Data Platforms Hands-on experience with Google BigQuery and Dataflow and Dataproc and Pub/Sub . Experience with Azure Synapse and Azure Data Factory . Experience with Amazon Redshift and AWS Glue . Data Processing &amp; Streaming Strong experience with Apache Spark and Apache Kafka . Experience building batch and real-time data processing pipelines. Data Transformation Hands-on experience with dbt or Oracle Data Integrator (ODI) for data transformation and orchestration. Experience implementing ETL/ELT best practices and reusable data models. Databases &amp; Data Warehousing Strong experience with Oracle or PostgreSQL . Expertise in SQL, relational database design, performance tuning, and query optimization. Data Engineering Experience with data modeling, data governance, metadata management, and data quality frameworks. Knowledge of dimensional modeling and modern data warehouse architectures. Preferred Skills Experience with cloud-native data lake and lakehouse architectures. Knowledge of CI/CD pipelines and Infrastructure as Code (IaC). Familiarity with containerization technologies such as Docker and Kubernetes. Experience supporting machine learning and analytics workloads. Cloud certifications on AWS, Microsoft Azure, or Google Cloud Platform are a plus. Key Technology Stack Google Cloud Data Services: BigQuery and Dataflow and Dataproc and Pub/Sub Azure Data Services: Azure Synapse and Azure Data Factory AWS Data Services: Amazon Redshift and AWS Glue Data Processing: Apache Spark and Apache Kafka Data Transformation: dbt or Oracle Data Integrator (ODI) Databases: Oracle or PostgreSQL Programming: SQL and Python Cloud Platforms: Google Cloud Platform or Microsoft Azure or Amazon Web Services (Preferred) Share</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"><b>Qualifications</b></p><p>Bachelor's degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or a related field.</p><p>3 11 years of professional experience in Data Engineering, Data Warehousing, or Big Data technologies.</p><p>Strong programming and scripting skills using SQL, Python, or similar languages.</p><p>Excellent analytical and problem-solving abilities.</p><p>Experience working in Agile/Scrum development environments.</p><p></p></section>

Established in 2008, Geidea epitomizes customer focused empowerment and commercial success through continuous innovation. Geidea makes best in class digital payment solutions available for all by attracting and leveraging the best creative & entrepreneurial talent in the market Our solutions give any business the chance to get ahead and reach for more no matter their size or maturity. Our technology mirrors our people - Smart, Innovative & Forward Thinkingwww.geidea.net<br><br>To maintain a competitive advantage as we grow, we are currently looking for a new " Senior Data Engineer"<br>.<br>Job purpose: to maintain a competitive advantage as we grow, we are looking for a highly skilled Senior Data Engineer to design, develop, and optimize scalable, secure, and high-performance data platforms across the enterprise. This role will play a key part in building and maintaining the data ecosystem that supports our Fintech services, including real-time financial transactions, credit scoring models, regulatory reporting, and customer analytics. The Senior Data Engineer will work closely with Data Architects, Software Engineers, Product Teams, and Data Analysts to develop modern data solutions leveraging Big Data technologies, Data Lakes, ELT/ETL pipelines, and Cloud Data Warehouses while ensuring reliability, security, governance, and regulatory complianc<br>e.<br>Responsibilities:Data Engineering & Platform Development Design, build, and maintain scalable data pipelines for batch and real-time data processing. Develop and optimize data ingestion frameworks from internal and external data sources. Implement and maintain data models to support analytics, reporting, and operational use cases. Collaborate with Data Architects to translate architectural designs into production-ready solutions. Big Data & Distributed Processing Develop and maintain large-scale data processing solutions using technologies such as Apache Spark, Databricks, Flink, Trino, or Presto. Build and optimize distributed data processing workloads handling high-volume financial and behavioral datasets. Work with distributed storage systems including S3, ADLS, HDFS, and related cloud-native services. Optimize data formats such as Parquet, ORC, and Avro for performance and storage efficiency. Data Lakes & Lakehouse Solutions Build and maintain Data Lake and Lakehouse environments using technologies such as Delta Lake, Apache Hudi, or Apache Iceberg. Implement data quality, partitioning, schema evolution, and lifecycle management processes. Support data governance and metadata management initiatives across all data layers. ELT/ETL Development Design, develop, and support robust ELT/ETL pipelines using tools such as Apache Airflow, DBT, AWS Glue, Azure Data Factory, or Kafka Connect. Develop reusable and maintainable transformation logic using SQL, Python, or Scala. Ensure pipeline reliability through monitoring, alerting, logging, and automated recovery mechanisms. Optimize data processing performance and cost efficiency. Data Warehousing & Analytics Enablement Develop and maintain cloud-based data warehouse solutions such as Snowflake, Redshift, Big Query, or Synapse Analytics. Build and optimize dimensional models, fact tables, and data marts to support business intelligence and reporting requirements. Collaborate with analytics teams to ensure efficient access to trusted and governed data assets. Support integration with BI platforms such as Power BI, Tableau, and Looker. Security, Governance & Compliance Implement data security controls including encryption, masking, tokenization, and access management. Ensure compliance with SAMA, NCA, GDPR, and internal security policies. Support data lineage, auditing, and governance initiatives through integration with metadata and cataloging solutions. Participate in data quality and governance programs to ensure accuracy and consistency of enterprise data. Dev Ops & Observability Contribute to CI/CD pipelines and Infrastructure as Code implementations using Terraform, Cloud Formation, or similar tools. Implement monitoring and observability solutions for data pipelines and platforms. Establish and maintain SLAs, data quality checks, and operational dashboards using tools such as Grafana, Prometheus, or Datadog. Troubleshoot production issues and provide performance tuning recommendatio<br>ns.<br>Qualifications:Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related technical field.5+ years of experience in Data Engineering, with hands-on experience building and supporting production-grade data platforms. Strong experience with Big Data technologies such as Apache Spark, Databricks, Flink, or similar distributed processing frameworks. Proven experience building and maintaining Data Lakes, Lakehouse architectures, and cloud-based data platforms. Strong proficiency in SQL and at least one programming language such as Python, Scala, or Java. Experience developing ELT/ETL pipelines using Airflow, DBT, AWS Glue, Azure Data Factory, or equivalent tools. Hands-on experience with cloud platforms such as AWS, Azure, or GCP. Experience with cloud data warehouses including Snowflake, Redshift, Big Query, or Synapse. Understanding of data governance, security, and regulatory requirements within Fintech, Banking, or highly regulated environments. Experience working with CI/CD, Infrastructure as Code, and monitoring tools is highly prefer<br>red.<br>Our values guide how we think and act - They describe what we care about the most Customer first - It’s embedded in our design thinking and customer service approach Open - Openness allows us to constantly improve and evolve Real - No jargon and no excuses! Bold - Constantly challenging ourselves and our way of thinking. Resilient – If we fail, we bounce back stronger than before. Collaborative - We know that we can achieve a lot more as a team. We are changing lives by constantly striving for a better solu<br>tion.

Established in 2008, Geidea epitomizes customer focused empowerment and commercial success through continuous innovation. Geidea makes best in class digital payment solutions available for all by attracting and leveraging the best creative & entrepreneurial talent in the market Our solutions give any business the chance to get ahead and reach for more no matter their size or maturity. Our technology mirrors our people - Smart, Innovative & Forward Thinkingwww.geidea.net<br><br>To maintain a competitive advantage as we grow, we are currently looking for a new " Senior Data Engineer"<br>.<br>Job purpose: to maintain a competitive advantage as we grow, we are looking for a highly skilled Senior Data Engineer to design, develop, and optimize scalable, secure, and high-performance data platforms across the enterprise. This role will play a key part in building and maintaining the data ecosystem that supports our Fintech services, including real-time financial transactions, credit scoring models, regulatory reporting, and customer analytics. The Senior Data Engineer will work closely with Data Architects, Software Engineers, Product Teams, and Data Analysts to develop modern data solutions leveraging Big Data technologies, Data Lakes, ELT/ETL pipelines, and Cloud Data Warehouses while ensuring reliability, security, governance, and regulatory complianc<br>e.<br>Responsibilities:Data Engineering & Platform Development Design, build, and maintain scalable data pipelines for batch and real-time data processing. Develop and optimize data ingestion frameworks from internal and external data sources. Implement and maintain data models to support analytics, reporting, and operational use cases. Collaborate with Data Architects to translate architectural designs into production-ready solutions. Big Data & Distributed Processing Develop and maintain large-scale data processing solutions using technologies such as Apache Spark, Databricks, Flink, Trino, or Presto. Build and optimize distributed data processing workloads handling high-volume financial and behavioral datasets. Work with distributed storage systems including S3, ADLS, HDFS, and related cloud-native services. Optimize data formats such as Parquet, ORC, and Avro for performance and storage efficiency. Data Lakes & Lakehouse Solutions Build and maintain Data Lake and Lakehouse environments using technologies such as Delta Lake, Apache Hudi, or Apache Iceberg. Implement data quality, partitioning, schema evolution, and lifecycle management processes. Support data governance and metadata management initiatives across all data layers. ELT/ETL Development Design, develop, and support robust ELT/ETL pipelines using tools such as Apache Airflow, DBT, AWS Glue, Azure Data Factory, or Kafka Connect. Develop reusable and maintainable transformation logic using SQL, Python, or Scala. Ensure pipeline reliability through monitoring, alerting, logging, and automated recovery mechanisms. Optimize data processing performance and cost efficiency. Data Warehousing & Analytics Enablement Develop and maintain cloud-based data warehouse solutions such as Snowflake, Redshift, Big Query, or Synapse Analytics. Build and optimize dimensional models, fact tables, and data marts to support business intelligence and reporting requirements. Collaborate with analytics teams to ensure efficient access to trusted and governed data assets. Support integration with BI platforms such as Power BI, Tableau, and Looker. Security, Governance & Compliance Implement data security controls including encryption, masking, tokenization, and access management. Ensure compliance with SAMA, NCA, GDPR, and internal security policies. Support data lineage, auditing, and governance initiatives through integration with metadata and cataloging solutions. Participate in data quality and governance programs to ensure accuracy and consistency of enterprise data. Dev Ops & Observability Contribute to CI/CD pipelines and Infrastructure as Code implementations using Terraform, Cloud Formation, or similar tools. Implement monitoring and observability solutions for data pipelines and platforms. Establish and maintain SLAs, data quality checks, and operational dashboards using tools such as Grafana, Prometheus, or Datadog. Troubleshoot production issues and provide performance tuning recommendatio<br>ns.<br>Qualifications:Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related technical field.5+ years of experience in Data Engineering, with hands-on experience building and supporting production-grade data platforms. Strong experience with Big Data technologies such as Apache Spark, Databricks, Flink, or similar distributed processing frameworks. Proven experience building and maintaining Data Lakes, Lakehouse architectures, and cloud-based data platforms. Strong proficiency in SQL and at least one programming language such as Python, Scala, or Java. Experience developing ELT/ETL pipelines using Airflow, DBT, AWS Glue, Azure Data Factory, or equivalent tools. Hands-on experience with cloud platforms such as AWS, Azure, or GCP. Experience with cloud data warehouses including Snowflake, Redshift, Big Query, or Synapse. Understanding of data governance, security, and regulatory requirements within Fintech, Banking, or highly regulated environments. Experience working with CI/CD, Infrastructure as Code, and monitoring tools is highly prefer<br>red.<br>Our values guide how we think and act - They describe what we care about the most Customer first - It’s embedded in our design thinking and customer service approach Open - Openness allows us to constantly improve and evolve Real - No jargon and no excuses! Bold - Constantly challenging ourselves and our way of thinking. Resilient – If we fail, we bounce back stronger than before. Collaborative - We know that we can achieve a lot more as a team. We are changing lives by constantly striving for a better solu<br>tion.

<p>Job Overview</p><p>We are seeking a motivated and analytical AI Data Engineer to join the AI4ALL Department on a part-time basis. This internship position offers hands-on experience in data engineering within a dynamic AI research and development environment. The successful candidate will collaborate with data science and software engineering teams to design, implement, and optimize data pipelines and infrastructure that enable scalable AI solutions.</p><p>About the Company</p><p>Our organization is dedicated to advancing accessible and responsible artificial intelligence. We foster an inclusive, collaborative culture that values curiosity, rigorous problem solving, and practical impact. Based in Egypt, we partner with regional and global teams to deliver AI-driven projects across industries, with a focus on education, healthcare, and enterprise solutions.</p><p>Key Responsibilities</p><ul><li>Design, build, and maintain robust data pipelines to collect, ingest, transform, and store large-scale datasets from diverse sources.</li><li>Collaborate with data scientists to understand data requirements, feature engineering needs, and model training workflows.</li><li>Implement data quality checks, monitoring, and validation processes to ensure data reliability and integrity.</li><li>Optimize ETL/ELT processes for performance, scalability, and cost-efficiency in cloud environments.</li><li>Assist in the development of data schemas, metadata catalogs, and data lineage documentation.</li><li>Contribute to data governance, security, and privacy compliance in accordance with organizational policies.</li><li>Participate in code reviews, testing, and documentation to support maintainable engineering practices.</li><li>Support deployment and operations of data infrastructure, including CI/CD pipelines for data workflows.</li></ul><p>Qualifications and Requirements</p><ul><li>Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field; pursuing or recently completed internship-focused program acceptable.</li><li>1 year of related experience in data engineering, data pipelines, or data integration.</li><li>Familiarity with programming languages commonly used in data engineering (Python, SQL; knowledge of Java/Scala a plus).</li><li>Experience with data processing frameworks and tools (e.g., Apache Spark, Apache Airflow, ETL/ELT platforms).</li><li>Understanding of relational and NoSQL databases, data modeling concepts, and cloud-based data services (AWS, GCP, or Azure).</li><li>Strong analytical and problem-solving skills with attention to detail and accuracy.</li><li>Excellent communication skills and ability to work collaboratively in a cross-functional team.</li><li>Eligibility to work in Egypt and availability for part-time commitment as per the internship schedule.</li></ul><p>Required Skills</p><ul><li>Data pipeline design and engineering</li><li>SQL and data querying optimization</li><li>Python programming for data engineering tasks</li><li>Experience with ETL/ELT tools and workflow orchestration (Airflow preferred)</li><li>Knowledge of cloud data services and basic data security practices</li><li>Strong communication and teamwork abilities</li></ul><p>Benefits and Perks</p><ul><li>Practical, hands-on experience with real-world AI data projects</li><li>Mentorship from experienced engineers and data scientists</li><li>Flexible, part-time schedule to accommodate academic commitments</li><li>Networking opportunities within a growing AI organization</li><li>Potential pathway to full-time opportunities based on performance</li></ul>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p><strong>Data Pipeline Development &amp; Infrastructure Design</strong></p><ul><li>Build, and maintain scalable data pipelines</li><li>Develop real-time and batch data processing frameworks for structured and unstructured data.</li><li>Implement ETL/ELT workflows to ingest data from various sources, ensuring high availability and performance .</li><li>Optimize data storage and retrieval of data in (near) real time and batch processes</li><li>Ensure cost-efficient and high-performance data infrastructure that scales with business needs.</li></ul><p><strong>Data Solutions &amp; AI-Driven Applications</strong></p><ul><li>Develop data pipelines for ML recommenders, search functionality, and AI-enhanced features .</li><li>Develop and maintain data models, APIs, and integrations to support analytics and customer applications.</li><li>Support eCommerce-related data solutions , including product recommendations, customer segmentation, and personalization models.</li></ul><p><strong>Collaboration &amp; Continuous Improvement</strong></p><ul><li>Work closely with Data Architects, Analysts, and Product Teams to understand data requirements and deliver best-in-class solutions.</li><li>Monitor and troubleshoot performance issues , ensuring high availability and efficiency of data pipelines.</li><li>Continuously optimize cost, performance, and scalability of data engineering solutions.</li></ul><p>At Sana Commerce we're committed to an inclusive environment and recognize that our diverse work orce is one of our greatest strengths. It all started in 2007, with a pizza and a plan. Sana Commerce is an e-commerce platform designed to help manufacturers, distributors and wholesalers succeed by fostering lasting relationships with customers who depend on them. We re a fast-growing SaaS company that allows you to take ownership of your career. We are looking for a Senior Data Engineer to design, build, and optimize our Azure and Databricks-based data infrastructure . You will play a critical role in developing scalable ETL pipelines, data ingestion frameworks, and contribute to AI/ML-powered solutions that drive internal decision-making and customer-facing insights. This is a hands-on role that requires expertise in Azure Data Services, Databricks, and Python/SQL . You will work closely with Data Architects, Engineers, and Product teams to develop robust data solutions that power analytics, personalization, and AI-driven customer experiences .</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>5+ years of experience as a Data Engineer , working with Apache Spark or bySpark.</li><li>Strong expertise in data pipeline development, ETL workflows, and real-time/batch data processing .</li><li>Experience in big data technologies, and large-scale data storage .</li><li>Familiarity with data governance, security, and compliance best practices and tools</li><li>Proficiency in Python, and SQL, for data transformation, data quality and automation.</li><li>Strong experience in optimizing data performance and cost-efficiency in cloud environments .</li><li><strong>Nice to Have</strong></li><li>Experience with eCommerce data solutions , such as customer segmentation, recommendation engines, and personalization models.</li><li>Knowledge of event-driven architectures, streaming data processing, and real-time analytics .</li><li>Familiarity with LLM-based AI applications and OpenAI or similar APIs .</li></ul><p></p></section>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span><b>Join Us</b> <br></span><p>At Vodafone, we’re not just shaping the future of connectivity for our customers – we’re shaping the future for everyone who joins our team. When you work with us, you’re part of a global mission to connect people, solve complex challenges, and create a sustainable and more inclusive world. If you want to grow your career whilst finding the perfect balance between work and life, Vodafone offers the opportunities to help you belong and make a real impact.</p><br><br><br><b>Role Profile</b> <br><p>The role primarily focuses (100%) on delivering end to end development solutions for BI and Big Data quality tasks, including pipelines, data trends and dashboards plus managing the system optimization, monitoring workflow performance, administering DWH applications and Big Data clusters, managing vendor communications, and handle system upgrades</p><br><br><br><b>Role Profile</b> <br><p><strong>Data Quality Management</strong></p><br> <p>&nbsp;Design, develop, and implement solutions to monitor, validate, and improve data accuracy, consistency, and completeness.</p><br> <ul> <li><strong>Pipeline Development &amp; Optimization</strong> Build data quality gates to ensure and maintain scalable data pipelines for processing and validating large datasets efficiently.</li> <li><strong>ETL &amp;Data integrations</strong><br>Develop and enhance ETL processes to ensure seamless data movement across systems while maintaining data quality dashboards End to End development flow</li> <li><strong>Data Governance &amp; Compliance</strong> – Ensure adherence to data governance policies, regulatory standards, and best practices for data management.</li> <li><strong>Root Cause Analysis &amp; Issue Resolution</strong> Investigate data anomalies, identify root causes, and implement corrective measures proactively.</li> <li><strong>Automation &amp; Monitoring</strong></li> </ul> <ul> <li><strong>Performance Tuning</strong></li> </ul> <p>&nbsp;Optimize query performance, database indexing, and system configurations to enhance efficiency.</p><br> <ul> <li><strong>Stakeholder Communication</strong></li> </ul> <p><strong>&nbsp;Work closely with data analysts, engineers, business teams, and vendors to ensure data quality objectives are met</strong></p><br> <p>Develop automation scripts and monitoring frameworks to streamline data quality checks and alert on anomalies</p><br><br><br><b>Competencies and Qualifications </b> <br><p>Understanding the Critical role in ensuring the quality, performance, and reliability of data solutions. The responsibilities and mindset should include:</p><br> <ul> <li><strong>Commitment to high data Quality</strong></li> </ul> <p>Passion for developing optimized code to ensure data quality to end user and develop the dashboards for analysis, optimizing performance, and applying a scientific approach to tuning and analysis.</p><br> <ul> <li>&nbsp;<strong>Agile Community Experience</strong></li> </ul> <p>&nbsp;Working in Agile teams in order to ensure delivering the needed quality gates and proactive actions</p><br> <ul> <li> <strong>Customer oriented Approach</strong></li> </ul> <p>&nbsp;A deep understanding of customer needs, ensuring that every developed feature and solution enhances the end user experience while proactively identifying and addressing potential issues before they arise. And committed to delivering solutions that enhance customer experience and satisfaction.</p><br> <p><span><strong>Must have technical / professional qualifications:</strong></span></p><br> <ul> <li>Bachelor of computer Science or related domains</li> <li>&nbsp;0 to 1 years in engineering, specifically in building quality gates for data pipelines, ensuring data accuracy, and administering distributed systems..</li> <li>Experience in bigdata systems and technologies such as Java, Python, NoSQL, Node.js, Angular, Kafka,Yarn,Hbase Zookeeper,Understanding of distributed systems like Hadoop (HDFS).</li> <li>Knowledge of data processing frameworks, such as Apache Hadoop (MapReduce), Apache Spark, Apache Apache Kafka.</li> <li>Understanding of data warehousing concepts and technologies Familiarity with ETL tools and processes for efficiently moving and transforming data</li> </ul><br><br><b>Not a perfect fit?</b> <br><p>Worried that you don’t meet all the desired criteria exactly? At Vodafone we are passionate about empowering people and creating a workplace where everyone can thrive, whatever their personal or professional background. If you’re excited about this role but your experience doesn’t align exactly with every part of the job description, we encourage you to still apply as you may be the right candidate for this role or another opportunity.</p><br><br><br><b>Who we are</b> <br><p>We are a leading international Telco, serving millions of customers. At Vodafone, we believe that connectivity is a force for good. If we use it for the things that really matter, it can improve people's lives and the world around us. Through our technology we empower people, connecting everyone regardless of who they are or where they live and we protect the planet, whilst helping our customers do the same.</p><br> <p>Belonging at Vodafone isn't a concept; it's lived, breathed, and cultivated through everything we do. You'll be part of a global and diverse community, with many different minds, abilities, backgrounds and cultures. ;We're committed to increase diversity, ensure equal representation, and make Vodafone a place everyone feels safe, valued and included.</p><br> <p>If you require any reasonable adjustments or have an accessibility request as part of your recruitment journey, for example, extended time or breaks in between online assessments, please refer to https://careers.vodafone.com/application-adjustments/ for guidance.</p><br> <p>Together we can.</p><br><br><br><br> </div>

Job Summary:We are seeking a Data Governance Engineer to join our UAE Technology Offshoring Team. The Ideal candidate will be responsible for the below:<br>Data Modeling with a strong understanding of data warehouse (DWH) concepts, data issues’ validation, and data mesh architecture and Star Schema<br>The ideal candidate should have hands-on experience with cloud platforms like Azure and Databricks, as well as data catalogue tools.<br>They should also be proficient in data quality tools and familiar with basic data engineering concepts, including data pipelines, ETL processes, and data lineage tracking.<br>Additionally, this role requires strong English and communication skills, as it involves working with diverse cultures and nationalities.<br>The candidate should be comfortable collaborating with cross-functional teams in an agile environment, documenting processes, and engaging with stakeholders across different domains.<br>Key Responsibilities:1. Data Modelling Management:Implement and maintain data governance frameworks, policies, and standards. Ensure high-quality data management across DWH models and data sources. Develop and execute data quality rules, validation processes, and monitoring frameworks. Identify and resolve data quality issues in collaboration with business and operation teams. Work with data quality tools to automate data validation and cleansing processes.2. Data Warehouse (DWH) & Data Modeling:Support the design and governance of data warehouse (DWH) models based on business requirements. Ensure data consistency and integrity across structured and semi-structured datasets. Collaborate with data architects and engineers to optimize DWH performance. Work with Data Mesh architecture to enable decentralized data ownership and governance.3. Cloud & Data Engineering Concepts:Utilize Databricks for Quality & Analytics. Understand ETL (Extract, Transform, Load) and ELT concepts for data ingestion pipelines. Support the development and governance of data pipelines using tools like Databricks or Apache Spark. Implement data lineage tracking to ensure data transparency and traceability across pipelines.4. Data Privacy & Compliance:Identification, classification, and protection of PII and sensitive data. Ensure compliance with data privacy regulations such as GDPR, CCPA, and local policies. Maintain data lineage and governance documentation.5. Agile & Squad-Based Collaboration:Work in an agile environment using the squad model. Collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders. Participate in sprint planning, backlog grooming, and agile ceremonies.6. Communication & Cross-Cultural Collaboration:Work with teams across different cultures and nationalities to align data governance strategies. Clearly communicate technical and governance concepts to both technical and non-technical stakeholders. Facilitate discussions, workshops, and training sessions to promote data governance best practices.<br>Required Skills & Qualifications:Experience in data governance, data quality, and data modeling Technical Expertise:Strong knowledge of data governance frameworks and data quality management. Experience with data warehouse (DWH) concepts and Data Mesh architecture. Knowledge of SQL, Python, or Spark Hand-on experience in IBM Tools Experience working with data quality tools Understanding of basic data engineering concepts, including ETL processes, data pipelines, and data lineage tracking. Experience with data catalog tools ( Azure Purview). Hands - on experience in Erwin<br>Data Privacy & Compliance:Understanding of PII identification, data classification, and regulatory compliance. Agile & Squad Methodology: Experience working in an agile environment with cross-functional squads. Strong English & Communication Skills:Strong verbal and written communication skills to engage with technical and business stakeholders.

Job Summary:We are seeking a Data Governance Engineer to join our UAE Technology Offshoring Team. The Ideal candidate will be responsible for the below:<br>Data Modeling with a strong understanding of data warehouse (DWH) concepts, data issues’ validation, and data mesh architecture and Star Schema<br>The ideal candidate should have hands-on experience with cloud platforms like Azure and Databricks, as well as data catalogue tools.<br>They should also be proficient in data quality tools and familiar with basic data engineering concepts, including data pipelines, ETL processes, and data lineage tracking.<br>Additionally, this role requires strong English and communication skills, as it involves working with diverse cultures and nationalities.<br>The candidate should be comfortable collaborating with cross-functional teams in an agile environment, documenting processes, and engaging with stakeholders across different domains.<br>Key Responsibilities:1. Data Modelling Management:Implement and maintain data governance frameworks, policies, and standards. Ensure high-quality data management across DWH models and data sources. Develop and execute data quality rules, validation processes, and monitoring frameworks. Identify and resolve data quality issues in collaboration with business and operation teams. Work with data quality tools to automate data validation and cleansing processes.2. Data Warehouse (DWH) & Data Modeling:Support the design and governance of data warehouse (DWH) models based on business requirements. Ensure data consistency and integrity across structured and semi-structured datasets. Collaborate with data architects and engineers to optimize DWH performance. Work with Data Mesh architecture to enable decentralized data ownership and governance.3. Cloud & Data Engineering Concepts:Utilize Databricks for Quality & Analytics. Understand ETL (Extract, Transform, Load) and ELT concepts for data ingestion pipelines. Support the development and governance of data pipelines using tools like Databricks or Apache Spark. Implement data lineage tracking to ensure data transparency and traceability across pipelines.4. Data Privacy & Compliance:Identification, classification, and protection of PII and sensitive data. Ensure compliance with data privacy regulations such as GDPR, CCPA, and local policies. Maintain data lineage and governance documentation.5. Agile & Squad-Based Collaboration:Work in an agile environment using the squad model. Collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders. Participate in sprint planning, backlog grooming, and agile ceremonies.6. Communication & Cross-Cultural Collaboration:Work with teams across different cultures and nationalities to align data governance strategies. Clearly communicate technical and governance concepts to both technical and non-technical stakeholders. Facilitate discussions, workshops, and training sessions to promote data governance best practices.<br>Required Skills & Qualifications:Experience in data governance, data quality, and data modeling Technical Expertise:Strong knowledge of data governance frameworks and data quality management. Experience with data warehouse (DWH) concepts and Data Mesh architecture. Knowledge of SQL, Python, or Spark Hand-on experience in IBM Tools Experience working with data quality tools Understanding of basic data engineering concepts, including ETL processes, data pipelines, and data lineage tracking. Experience with data catalog tools ( Azure Purview). Hands - on experience in Erwin<br>Data Privacy & Compliance:Understanding of PII identification, data classification, and regulatory compliance. Agile & Squad Methodology: Experience working in an agile environment with cross-functional squads. Strong English & Communication Skills:Strong verbal and written communication skills to engage with technical and business stakeholders.

Valleysoft is a regional IT services provider delivering enterprise application development, process management, IT support, and a broad range of technology solutions for global clients. Working across the information technology and services sector, the company helps organizations solve complex business problems through practical, scalable digital solutions.<br><br>As a Data Scientist - Artificial Intelligence, you will help shape AI-driven solutions that turn data into business value. This role is focused on applying advanced data science, machine learning, and generative AI techniques to real-world challenges, partnering closely with technical teams and business stakeholders to deliver solutions that are innovative, reliable, and aligned with business goals.<br><br>Responsibilities<br><br>Design, develop, and deploy Machine Learning and Artificial Intelligence models to address complex business challenges. Analyze large volumes of structured and unstructured data to identify trends, patterns, and actionable insights. Build predictive, classification, clustering, recommendation, and forecasting models. Develop and optimize Deep Learning models using modern AI frameworks. Design and implement Generative AI solutions using Large Language Models (LLMs). Build Retrieval-Augmented Generation (RAG) pipelines and apply Prompt Engineering techniques. Perform data collection, cleansing, preprocessing, feature engineering, and exploratory data analysis (EDA). Collaborate with Data Engineers and Software Engineers to build scalable AI applications and data pipelines. Deploy, monitor, and maintain machine learning models using MLOps best practices. Evaluate and improve model performance using appropriate statistical and machine learning metrics. Work closely with business stakeholders to translate business requirements into AI-driven solutions. Develop technical documentation, model documentation, and solution architecture artifacts. Ensure AI solutions comply with data governance, security, privacy, and Responsible AI principles. Stay current with emerging AI technologies, frameworks, and industry best practices<br><br>Requirements<br><br>Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related field. Min 7 years of hands-on experience in Data Science, Machine Learning, or Artificial Intelligence. Strong experience developing and deploying AI/ML models in enterprise environments. Excellent analytical, problem-solving, and communication skills. Experience working in Agile development environments. <br><br>Technical Skills:<br><br>Programming Languages<br><br> Python SQL R (Preferred) <br><br>Machine Learning & Data Science<br><br> Scikit-learn XGBoost Light GBM Statistical Modeling Predictive Analytics Time Series Forecasting Classification & Regression Clustering Recommendation Systems Feature Engineering <br><br>Deep Learning<br><br> Tensor Flow PyTorch Keras <br><br>Generative AI<br><br> Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Lang Chain Llama Index AI Agents Vector Databases (FAISS, Chroma DB, Pinecone) <br><br>IBM AI & Data Platform<br><br> IBM watsonx.ai IBM watsonx.data IBM watsonx.governance IBM Cloud Pak for Data IBM Knowledge Catalog IBM Db2 IBM SPSS Modeler (Preferred) <br><br>Data Engineering<br><br> Apache Spark Hadoop Apache Kafka Apache Airflow Pandas Num Py ETL Pipelines <br><br>Databases<br><br> Postgre SQL Oracle Database Microsoft SQL Server Mongo DB <br><br>Cloud Platforms<br><br> IBM Cloud Microsoft Azure Amazon Web Services (AWS) Google Cloud Platform (GCP) <br><br>MLOps & Dev Ops<br><br> MLflow Docker Kubernetes Git Jenkins CI/CD Pipelines <br><br>Data Visualization<br><br> Power BI Tableau Matplotlib Plotly <br><br>Preferred Skills<br><br> Experience developing enterprise AI solutions using IBM watsonx platform. Experience building AI-powered applications using LLMs and RAG architectures. Knowledge of Natural Language Processing (NLP) and Computer Vision. Experience with Explainable AI (XAI) and Responsible AI principles. Familiarity with Data Governance and AI Governance frameworks. Experience integrating AI models with REST APIs and microservices. Understanding of distributed computing and Big Data technologies. Experience working in Agile/Scrum teams. <br><br>Soft Skills<br><br> Strong analytical and critical thinking skills. Excellent problem-solving abilities. Strong verbal and written communication skills. Ability to work collaboratively within cross-functional teams. Strong stakeholder management skills. Ability to manage multiple priorities in a fast-paced environment. Passion for innovation, continuous learning, and emerging AI technologies. <br><br>Preferred Certifications<br><br> IBM watsonx AI Certification IBM AI Engineering Professional Certificate Microsoft Certified: Azure AI Engineer Associate AWS Certified Machine Learning - Specialty Google Professional Machine Learning Engineer Databricks Certified Machine Learning Professional <br><br>Benefits<br><br>Private Health Insurance Training & Development Opportunities for professional growth and development in a cutting-edge field A collaborative and inclusive work environment The chance to work on impactful projects with a team of passionate experts

Principal AI/ML Architect & Applied AI Lead Over 20 years of market experience, Intellias brings together technologists, creators, and innovators across Europe, North and Latin America, and the Middle East. Join our international team and help solve the advanced technology challenges of tomorrow.<br>Project Overview We are seeking a highly experienced and hands-on Principal AI/ML Architect & Applied AI Lead to drive the design, development, and operationalization of enterprise-scale AI systems across both research and production environments. This role combines deep expertise in Machine Learning, Generative AI, distributed data systems, and cloud-native architectures with strategic leadership capabilities. The ideal candidate will lead complex AI initiatives end-to-end — from experimentation and research to scalable deployment in global enterprise environments. The position requires a strong balance of:Technical leadership Hands-on implementation AI strategy and innovation Cross-functional collaboration Mentorship and team development<br>Requirements Education & Experience Master’s or Ph. D. in Computer Science, Data Science, Machine Learning, or a related field10+ years of experience in AI/ML, data science, distributed systems engineering, or related domains Proven experience designing and deploying production-grade AI solutions at enterprise scale Strong background in both research-driven and industrial AI environments Experience leading global or distributed technical teams Demonstrated success delivering enterprise AI transformation initiatives Technical Expertise AI / Machine Learning Large Language Models (LLMs) Generative AI systems NLP / NLU technologies Retrieval-Augmented Generation (RAG) Agentic AI workflows and orchestration frameworks AI governance and Responsible AI practices MLOps frameworks and operational AI systems Data Engineering & Distributed Systems Apache Spark Databricks Delta Lake SQL and NoSQL databases Distributed computing architectures Streaming and batch data pipelines Cloud & Infrastructure Azure and/or AWSDocker and Kubernetes CI/CD pipelines Infrastructure-as-Code (IaC) Cloud-native platform architecture Infrastructure optimization and cloud cost management Programming Python Scala Additional Qualifications Experience building AI platforms serving multiple teams or business units Experience operationalizing AI securely in enterprise environments Strong communication and stakeholder management skills Ability to translate complex technical concepts into business value Responsibilities AI Architecture & Strategy Lead the design and implementation of AI/ML solutions across multiple business domains Drive enterprise adoption of LLMs, Generative AI, NLP/NLU, and advanced analytics solutions Define AI architecture standards, MLOps best practices, and scalable deployment strategies Evaluate emerging AI technologies and identify opportunities for innovation and operational impact Translate research initiatives into production-ready AI solutions Data & Platform Engineering Architect scalable distributed data-processing systems for large-scale datasets and real-time pipelines Design and optimize cloud-native AI platforms using modern data engineering frameworks Lead cloud migration and modernization initiatives from on-premises environments to Azure and/or AWSImplement efficient data pipelines leveraging Spark, Delta Lake, Databricks, Kubernetes, and containerized environments Ensure reliability, scalability, observability, security, and cost-efficiency of AI infrastructure Generative AI & Conversational Systems Design and implement enterprise-grade chatbot and conversational AI platforms Lead development of RAG pipelines, agentic workflows, and LLM orchestration systems Define governance, evaluation, monitoring, and safety strategies for Gen AI systems Collaborate with research teams to operationalize LLM-based applications securely and responsibly Leadership & Collaboration Lead cross-functional teams composed of data scientists, ML engineers, software engineers, and business stakeholders Mentor engineers and researchers on AI/ML best practices, architecture, and software engineering standards Coordinate global AI initiatives across distributed teams and multiple geographies Communicate technical concepts effectively to executive and non-technical audiences Support innovation programs and AI adoption strategies across the organization What We Offer Opportunity to shape enterprise AI strategy at global scale Work on cutting-edge Generative AI and applied ML initiatives International and collaborative engineering environment Access to modern cloud-native and AI technologies Professional growth, leadership exposure, and innovation-driven culture

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p><strong>Job Description:</strong> The Data Quality Engineer is responsible for designing, implementing, and maintaining enterprise-scale data quality solutions using Databricks , PySpark , and Delta Lake . This role focuses on building automated data profiling, validation, cleansing, monitoring, and remediation capabilities across modern data platforms while ensuring high levels of data integrity, consistency, and reliability. Working closely with data engineers, data architects, governance teams, business stakeholders, and analytics teams, the Data Quality Engineer will develop scalable data quality frameworks, AI-assisted profiling solutions, reusable rule engines, and automated quality monitoring processes that support trusted data products throughout the organization's data lifecycle.</p><p><strong>Key Responsibilities:</strong></p><ul><li>Configure, administer, and maintain the Databricks workspace to support enterprise data quality initiatives.</li><li>Provision and manage Databricks compute clusters, notebooks, Delta Lake structures, and Unity Catalog integration.</li><li>Develop AI-assisted data profiling notebooks using PySpark to establish baseline data quality measurements across enterprise datasets.</li><li>Analyze and measure data quality across key dimensions, including:<ul><li>Completeness</li><li>Uniqueness</li><li>Validity</li><li>Consistency</li><li>Accuracy</li><li>Timeliness</li></ul></li><li>Design, develop, and maintain a scalable Data Quality Rule Factory using parameterized PySpark templates.</li><li>Create reusable data quality rules that can be deployed across multiple datasets without manual rule development.</li><li>Integrate data quality validation into Bronze Silver Gold Delta Lake pipelines.</li><li>Implement automated quality gates to prevent low-quality data from progressing through data processing layers.</li><li>Design and develop automated data cleansing pipelines using PySpark transformations.</li><li>Implement data standardization, deduplication, schema harmonization, and data normalization processes.</li><li>Develop and deploy MLflow-managed machine learning models for anomaly detection and duplicate identification.</li><li>Ensure AI-generated recommendations are explainable and support human review before implementation.</li><li>Design and implement exception handling and quarantine mechanisms for records failing quality validation.</li><li>Capture detailed exception metadata, including:<ul><li>Failure reason</li><li>Rule reference</li><li>Affected data element</li><li>Processing timestamp</li></ul></li><li>Build automated reprocessing workflows for corrected or remediated records.</li><li>Develop Delta Lake aggregation tables to support enterprise reporting and dashboarding of data quality metrics.</li><li>Produce quality metrics including:<ul><li>Data Quality Scores</li><li>Rule Pass Rates</li><li>SLA Compliance</li><li>Trend Analysis</li></ul></li><li>Configure threshold-based alerts using Databricks SQL Alerts and Azure Monitor integration.</li><li>Develop predictive analytics models to identify datasets at risk of future quality degradation.</li><li>Support business and technical teams by performing AI-assisted root cause analysis and identifying recurring data quality issues.</li><li>Generate prioritized remediation recommendations based on detected quality patterns.</li><li>Collaborate with data engineers, architects, governance teams, and business stakeholders to improve enterprise data quality.</li><li>Optimize PySpark jobs and Delta Lake workloads for scalability and performance.</li><li>Develop technical documentation, operational procedures, and best practices for enterprise data quality management.</li><li>Participate in code reviews, testing, deployment, and continuous improvement of data quality frameworks.</li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related technical field.</li><li>Proven experience developing enterprise data quality solutions using Databricks and PySpark .</li><li>Strong hands-on experience with Delta Lake architecture and Medallion (Bronze, Silver, Gold) data pipelines.</li><li>Experience building automated ETL/ELT workflows using Databricks.</li><li>Strong knowledge of data quality principles, profiling methodologies, and validation techniques.</li><li>Experience designing reusable rule-based validation frameworks and scalable data quality engines.</li><li>Hands-on experience developing PySpark notebooks and optimizing distributed data processing workloads.</li><li>Experience implementing automated data cleansing, transformation, deduplication, and schema harmonization processes.</li><li>Experience working with Unity Catalog for data governance and metadata management.</li><li>Familiarity with MLflow for machine learning model lifecycle management.</li><li>Knowledge of machine learning techniques for anomaly detection, duplicate identification, and predictive analytics is highly desirable.</li><li>Experience implementing exception handling, quarantine processes, and automated data remediation workflows.</li><li>Familiarity with Databricks SQL Alerts, Azure Monitor, and enterprise monitoring solutions.</li><li>Strong understanding of relational databases, data warehouses, and modern lakehouse architectures.</li><li>Experience developing dashboards and reporting datasets for monitoring data quality KPIs.</li><li>Strong SQL skills and experience working with large-scale structured and semi-structured datasets.</li><li>Understanding of data governance, metadata management, and enterprise data management best practices.</li><li>Excellent analytical, troubleshooting, and problem-solving skills.</li><li>Strong communication skills with the ability to work effectively across technical and business teams.</li><li>Experience working in Agile or Scrum delivery environments is preferred.</li><li>Databricks, Microsoft Azure, Apache Spark, or related cloud data engineering certifications are highly desirable.</li></ul><p></p></section>

<p><h4>Join us</h4> <p>At Vodafone, we’re not just shaping the future of connectivity for our customers – we’re shaping the future for everyone who joins our team. When you work with us, you’re part of a global mission to connect people, solve complex challenges, and create a sustainable and more inclusive world. If you want to grow your career whilst finding the perfect balance between work and life, Vodafone offers the opportunities to help you belong and make a real impact.</p> <h4>Role profile</h4> <p>The role primarily focuses (100%) on delivering end to end development solutions for BI and Big Data quality tasks, including pipelines, data trends and dashboards plus managing the system optimization, monitoring workflow performance, administering DWH applications and Big Data clusters, managing vendor communications, and handling system upgrades.</p> <h4>Data quality management</h4> <ul> <li>Design, develop, and implement solutions to monitor, validate, and improve data accuracy, consistency, and completeness.</li> </ul> <h4>Pipeline development & optimization</h4> <ul> <li>Build data quality gates to ensure and maintain scalable data pipelines for processing and validating large datasets efficiently.</li> </ul> <h4>ETL & data integrations</h4> <ul> <li>Develop and enhance ETL processes to ensure seamless data movement across systems while maintaining data quality dashboards end to end development flow.</li> </ul> <h4>Data governance & compliance</h4> <ul> <li>Ensure adherence to data governance policies, regulatory standards, and best practices for data management.</li> </ul> <h4>Root cause analysis & issue resolution</h4> <ul> <li>Investigate data anomalies, identify root causes, and implement corrective measures proactively.</li> </ul> <h4>Automation & monitoring</h4> <ul> <li>Develop automation scripts and monitoring frameworks to streamline data quality checks and alert on anomalies.</li> </ul> <h4>Performance tuning</h4> <ul> <li>Optimize query performance, database indexing, and system configurations to enhance efficiency.</li> </ul> <h4>Stakeholder communication</h4> <ul> <li>Work closely with data analysts, engineers, business teams, and vendors to ensure data quality objectives are met.</li> </ul> <h4>Competencies and qualifications</h4> <p>Understanding the critical role in ensuring the quality, performance, and reliability of data solutions. The responsibilities and mindset should include:</p> <ul> <li><strong>Commitment to high data quality</strong><br> Passion for developing optimized code to ensure data quality to end user and develop the dashboards for analysis, optimizing performance, and applying a scientific approach to tuning and analysis.</li> <li><strong>Agile community experience</strong><br> Working in Agile teams in order to ensure delivering the needed quality gates and proactive actions.</li> <li><strong>Customer oriented approach</strong><br> A deep understanding of customer needs, ensuring that every developed feature and solution enhances the end user experience while proactively identifying and addressing potential issues before they arise. Committed to delivering solutions that enhance customer experience and satisfaction.</li> </ul> <h4>Must have technical / professional qualifications</h4> <ul> <li>Bachelor of Computer Science or related domains.</li> <li>0 to 1 years in engineering, specifically in building quality gates for data pipelines, ensuring data accuracy, and administering distributed systems.</li> <li>Experience in Big Data systems and technologies such as Java, Python, NoSQL, Node.js, Angular, Kafka, Yarn, HBase, Zookeeper, and understanding of distributed systems like Hadoop (HDFS).</li> <li>Knowledge of data processing frameworks, such as Apache Hadoop (MapReduce), Apache Spark, Apache Kafka.</li> <li>Understanding of data warehousing concepts and technologies.</li> <li>Familiarity with ETL tools and processes for efficiently moving and transforming data.</li> </ul> <h4>Not a perfect fit?</h4> <p>Worried that you don’t meet all the desired criteria exactly? At Vodafone we are passionate about empowering people and creating a workplace where everyone can thrive, whatever their personal or professional background. If you’re excited about this role but your experience doesn’t align exactly with every part of the job description, we encourage you to still apply as you may be the right candidate for this role or another opportunity.</p> <h4>Who we are</h4> <p>We are a leading international Telco, serving millions of customers. At Vodafone, we believe that connectivity is a force for good. If we use it for the things that really matter, it can improve people's lives and the world around us. Through our technology we empower people, connecting everyone regardless of who they are or where they live and we protect the planet, whilst helping our customers do the same.</p> <p>Belonging at Vodafone isn't a concept; it's lived, breathed, and cultivated through everything we do. You'll be part of a global and diverse community, with many different minds, abilities, backgrounds and cultures. We're committed to increase diversity, ensure equal representation, and make Vodafone a place everyone feels safe, valued and included.</p> <h4>Accessibility</h4> <p>If you require any reasonable adjustments or have an accessibility request as part of your recruitment journey, for example, extended time or breaks in between online assessments, please refer to the relevant guidance provided by Vodafone.</p> <p>Together we can.</p></p><p></p>

<p><h4>Connect to your career at Deloitte</h4> <p>Deloitte, established globally in 1845, is the world’s largest and leading professional services firm, providing audit & assurance, tax & legal, and consulting and related services to public and private clients spanning multiple industries. Present in more than 150 countries, Deloitte is distinct in its ability to help clients solve their most complex problems, from strategy to implementation.</p> <p>Deloitte Innovation Hub (DIH) is a strategic initiative established to support our ambition to become the leading business transformation partner of choice for our clients and to expand and scale our delivery footprint across EMEA. With access to a scaled, diverse, highly skilled, motivated, and engaged workforce, DIH is delivering complex technical solutions for clients’ most complex business problems, across portfolios that include ‘Strategy & Transactions’, ‘Customer’, ‘Engineering, AI & Data’, ‘Enterprise, Technology & Performance’ and ‘Cyber’. DIH is aiming to become the destination for top talents in Egypt for a long, exciting career.</p> <p>We invest in outstanding people of diverse talents and backgrounds and empower them to achieve more than they could elsewhere. Our work combines advice with action and integrity. We believe that when our clients and society are stronger, so are we. Our organization has grown in scale and diversity, providing services across the region, with our shared culture remaining the same. We aim to help clients realize their ambitions, make a positive difference in society, and maximize the success of our people. This drive fuels the commitment and humanity that run deep through our every action.</p> <h4>Connect to your opportunity</h4> <ul> <li>Identify and solve complex problems using a structured and logical approach.</li> <li>Stay up to date on the latest data engineering technologies and trends.</li> <li>Work with other engineering teams to integrate data engineering solutions with other systems.</li> <li>Maintain and optimize data systems to ensure high availability and performance.</li> <li>Design and implement data pipelines to collect, transform, and load data into data warehouses and data lakes.</li> <li>Gather requirements from stakeholders and translate them into technical specifications.</li> <li>Lead a team of data engineers in the design, development, and implementation of data engineering solutions.</li> <li>Manage functional and non-functional requirements and have a deep understanding of systems engineering methodologies.</li> <li>Build and maintain positive relationships with stakeholders, and effectively communicate technical concepts to non-technical audiences.</li> <li>Manage multiple projects simultaneously in a highly organized and efficient manner.</li> <li>Think creatively and come up with new solutions to problems.</li> <li>Communicate effectively with technical and non-technical audiences, both verbally and in writing.</li> </ul> <h4>Connect to your skills and professional experience</h4> <ul> <li><strong>Technical skills:</strong> 7+ years of relevant experience.</li> <li><strong>Cloud computing platforms:</strong> AWS / Azure / GCP</li> <li><strong>Programming languages:</strong> Python / Java / Scala & Unix Shell scripting</li> <li><strong>Data warehouse technologies:</strong> Redshift / Snowflake / BigQuery</li> <li><strong>Data lake technologies:</strong> Hadoop, Apache Beam, Spark, and Hive</li> <li><strong>Orchestration:</strong> Airflow / Control-M / (Any orchestration tool)</li> <li><strong>Machine learning frameworks:</strong> TensorFlow, PyTorch, and scikit-learn</li> </ul> <h4>Connect to your service line - Technology & Transformation</h4> <p>Distinctive thinking, deep expertise, and collaborative working. That’s what connects us. That’s what makes us Deloitte. If you want to help solve some of the biggest challenges around, join us. Together, we’ll make an impact that matters.</p> <h4>Personal independence</h4> <p>Regulation and controls are standard practice in our industry and Deloitte is no exception. These controls provide important legal protection for both you and the firm. We are subject to several audit regulations, one of which requires that certain colleagues abide by specific personal independence constraints. This can mean that you and your immediate family members are not permitted to hold certain financial interests (shares, funds, bonds etc.) with audit clients of the firm. The recruitment team will provide further detail as you progress through the recruitment process.</p> <h4>Connect to your industry</h4> <p>“What attracted me to Deloitte were the endless opportunities and the collective experience of other like-minded individuals. Deloitte’s clients include many of the world’s largest organisations; I wanted to be part of a team that made a difference that I could be proud of.”<br><strong>- Dan, Technology and Transformation</strong></p> <h4>Our commitment to you</h4> <p>Making an impact is more than just what we do: it’s why we’re here. So we work hard to create an environment where you can experience a purpose you believe in, the freedom to be you, and the capacity to go further than ever before.</p> <p>We want you. The true you. Your own strengths, perspective, and personality. So, we’re nurturing a culture where everyone belongs, feels supported and heard, and is empowered to make a valuable, personal contribution. You can be sure we’ll take your wellbeing seriously, too. Because it’s only when you’re comfortable and at your best that you can make the kind of impact you, and we, live for.</p> <p>Your expertise is our capability, so we’ll make sure it never stops growing. Whether it’s from the complex work you do, or the people you collaborate with, you’ll learn every day. Through world-class development, you’ll gain invaluable technical and personal skills. Whatever your level, you’ll learn how to lead.</p> <h4>Connect to your next step</h4> <p>A career at Deloitte is an opportunity to develop in any direction you choose. Join us and you’ll experience a purpose you can believe in and an impact you can see. You’ll be free to bring your true self to work every day. And you’ll never stop growing, whatever your level.</p></p><p></p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><b><strong>About Mozn</strong></b></p><br><p><span>MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.</span><br><span>We’re a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact.</span><br><span>If you’re passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.</span><br></p><br><p><b><strong>About the role</strong></b></p><br><p><span>We are looking for a highly motivated Cloud Platform Engineer III to join our Cloud Engineering team. The ideal candidate is passionate about data reliability, performance, and scalable backing services.</span></p><br><p><span>This role focuses on the reliability, performance, operation, automation, and continuous improvement of critical backing services such as MySQL, PostgreSQL, MongoDB, Elasticsearch/OpenSearch, Kafka, analytical databases (e.g., StarRocks, ClickHouse), and other database and messaging technologies across cloud-native and hybrid environments.</span></p><br><p><span>This is not a traditional DBA role. The ideal candidate understands distributed systems, Kubernetes, cloud platforms, automation, IaC, observability, and AI-assisted workflows, and can help product engineering teams use backing services safely and effectively.</span></p><br><p><b><strong>What you'll do</strong></b></p><br><p><b><strong>Data Reliability &amp; Backing Services Operations</strong></b></p><br><ul><li><span>Own reliability, performance, scalability, and operational health of MySQL, PostgreSQL, MongoDB, Elasticsearch/OpenSearch, Kafka, StarRocks, ClickHouse, and similar platforms.</span></li></ul><ul><li><span>Define best practices for how product engineering teams use transactional, document, search, messaging, and analytical platforms.</span></li></ul><ul><li><span>Design and maintain highly available, scalable, and resilient platform services, including replication, backup, recovery, failover, and disaster recovery capabilities.</span></li></ul><ul><li><span>Perform capacity planning, performance tuning, workload reviews, upgrades, patching, and lifecycle management for platform services.</span></li></ul><ul><li><span>Identify and resolve risks such as slow queries, hot partitions, consumer lag, replication lag, index growth, retention issues, and storage saturation.</span></li></ul><ul><li><span>Troubleshoot and resolve complex production issues related to databases, messaging systems, search platforms, and distributed data platforms.</span></li></ul><p><b><strong>Kubernetes &amp; Cloud Platform Engineering</strong></b></p><br><ul><li><span>Hands-on experience deploying, operating, and troubleshooting stateful workloads in Kubernetes-based environments.</span></li></ul><ul><li><span>Strong understanding of Kubernetes fundamentals, including networking, storage, workload lifecycle management, scalability, and reliability concepts.</span></li></ul><ul><li><span>Enable and support Kubernetes-based deployments of database, messaging, search, and analytical platforms using cloud-native patterns and operational best practices.</span></li></ul><p><b><strong>Automation &amp; Platform Enablement</strong></b></p><br><ul><li><span>Use automation, Infrastructure as Code, GitOps, and CI/CD to make backing services repeatable, reliable, and easier to operate.</span></li></ul><ul><li><span>Contribute to self-service platform capabilities, guardrails, dashboards, alerts, runbooks, and production readiness checks.</span></li></ul><ul><li><span>Use AI-assisted workflows where appropriate for incident triage, root cause analysis, query analysis, capacity forecasting, documentation, and developer support.</span></li></ul><ul><li><span>Collaborate with Product Engineering, SRE, Security, Data Engineering, and Cloud Platform teams to improve reliability, performance, availability, and security posture.</span></li></ul><p><b><strong>Qualifications</strong></b></p><br><ul><li><span>4-7 years of experience in Platform Engineering, SRE, Database Reliability Engineering, Data Platform Engineering, DevOps, or related roles.</span></li></ul><ul><li><span>Strong hands-on experience with MySQL, PostgreSQL, Kafka, and at least one of MongoDB or Elasticsearch/OpenSearch in production environments.</span></li></ul><ul><li><span>Experience with analytical or distributed data platforms such as StarRocks, ClickHouse, Apache Doris, Druid, Pinot, or similar OLAP systems is highly desirable.</span></li></ul><ul><li><span>Hands-on experience operating stateful workloads in Kubernetes-based environments.</span></li></ul><ul><li><span>Good understanding of high availability, replication, backup and recovery, disaster recovery, capacity planning, and performance tuning concepts.</span></li></ul><ul><li><span>Familiarity with distributed systems concepts including sharding, replication, partitioning, consistency, compaction, backpressure, consumer lag, and query optimization.</span></li></ul><ul><li><span>Experience with at least one major cloud platform (AWS, GCP, or OCI).</span></li></ul><ul><li><span>Experience automating provisioning, deployment, configuration, monitoring, and lifecycle management using tools such as Terraform, Helm, Ansible, GitOps, or similar automation frameworks.</span></li></ul><ul><li><span>Strong scripting or programming skills in Python, Bash, Go, or similar.</span></li></ul><ul><li><span>Experience with observability platforms such as LTGM, Prometheus/Grafana, ELK/OpenSearch, Datadog, or equivalent.</span></li></ul><ul><li><span>Strong troubleshooting, problem-solving, and debugging skills across distributed systems.</span></li></ul><ul><li><span>Excellent communication, collaboration, and documentation skills.</span></li></ul><ul><li><span>Demonstrated curiosity, ownership mindset, adaptability, and ability to guide product engineering teams.</span></li></ul><p><b><strong>Preferred Qualifications</strong></b></p><br><ul><li><span>Experience designing, operating, or optimizing large-scale distributed database, messaging, search, or analytics platforms.</span></li></ul><ul><li><span>Experience operating or optimizing analytical databases and OLAP systems such as StarRocks, ClickHouse, Apache Doris, Druid, or Pinot.</span></li></ul><ul><li><span>Experience with streaming and real-time data platforms leveraging technologies such as Kafka, Flink, Spark, CDC, or similar ecosystems.</span></li></ul><ul><li><span>Exposure to Analytics, Data Engineering, AI/ML platforms, LLM-based applications, or AI infrastructure projects.</span></li></ul><ul><li><span>Experience using AI-assisted tooling or agents to improve operations, troubleshooting, documentation, or developer self-service.</span></li></ul> </div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>We are looking for a highly motivated Cloud Platform Engineer to join our Cloud Engineering team. The ideal candidate is passionate about data reliability, performance, and scalable backing services. This role focuses on the reliability, performance, operation, automation, and continuous improvement of critical backing services such as MySQL, PostgreSQL, MongoDB, Elasticsearch/OpenSearch, Kafka, analytical databases (e.g., StarRocks, ClickHouse), and other database and messaging technologies across cloud-native and hybrid environments. This is not a traditional DBA role. The ideal candidate understands distributed systems, Kubernetes, cloud platforms, automation, IaC, observability, and AI-assisted workflows, and can help product engineering teams use backing services safely and effectively.</p><p><b>What you'll do</b></p><p>Data Reliability &amp; Backing Services Operations</p><ul><li>Own reliability, performance, scalability, and operational health of MySQL, PostgreSQL, MongoDB, Elasticsearch/OpenSearch, Kafka, StarRocks, ClickHouse, and similar platforms.</li><li>Define best practices for how product engineering teams use transactional, document, search, messaging, and analytical platforms.</li><li>Design and maintain highly available, scalable, and resilient platform services, including replication, backup, recovery, failover, and disaster recovery capabilities.</li><li>Perform capacity planning, performance tuning, workload reviews, upgrades, patching, and lifecycle management for platform services.</li><li>Identify and resolve risks such as slow queries, hot partitions, consumer lag, replication lag, index growth, retention issues, and storage saturation.</li><li>Troubleshoot and resolve complex production issues related to databases, messaging systems, search platforms, and distributed data platforms.</li></ul><p>Kubernetes &amp; Cloud Platform Engineering</p><ul><li>Hands-on experience deploying, operating, and troubleshooting stateful workloads in Kubernetes-based environments.</li><li>Strong understanding of Kubernetes fundamentals, including networking, storage, workload lifecycle management, scalability, and reliability concepts.</li><li>Enable and support Kubernetes-based deployments of database, messaging, search, and analytical platforms using cloud-native patterns and operational best practices.</li></ul><p>Automation &amp; Platform Enablement</p><ul><li>Use automation, Infrastructure as Code, GitOps, and CI/CD to make backing services repeatable, reliable, and easier to operate.</li><li>Contribute to self-service platform capabilities, guardrails, dashboards, alerts, runbooks, and production readiness checks.</li><li>Use AI-assisted workflows where appropriate for incident triage, root cause analysis, query analysis, capacity forecasting, documentation, and developer support.</li><li>Collaborate with Product Engineering, SRE, Security, Data Engineering, and Cloud Platform teams to improve reliability, performance, availability, and security posture.</li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>4-7 years of experience in Platform Engineering, SRE, Database Reliability Engineering, Data Platform Engineering, DevOps, or related roles.</li><li>Strong hands-on experience with MySQL, PostgreSQL, Kafka, and at least one of MongoDB or Elasticsearch/OpenSearch in production environments.</li><li>Experience with analytical or distributed data platforms such as StarRocks, ClickHouse, Apache Doris, Druid, Pinot, or similar OLAP systems is highly desirable.</li><li>Hands-on experience operating stateful workloads in Kubernetes-based environments.</li><li>Good understanding of high availability, replication, backup and recovery, disaster recovery, capacity planning, and performance tuning concepts.</li><li>Familiarity with distributed systems concepts including sharding, replication, partitioning, consistency, compaction, backpressure, consumer lag, and query optimization.</li><li>Experience with at least one major cloud platform (AWS, GCP, or OCI).</li><li>Experience automating provisioning, deployment, configuration, monitoring, and lifecycle management using tools such as Terraform, Helm, Ansible, GitOps, or similar automation frameworks.</li><li>Strong scripting or programming skills in Python, Bash, Go, or similar.</li><li>Experience with observability platforms such as LTGM, Prometheus/Grafana, ELK/OpenSearch, Datadog, or equivalent.</li><li>Strong troubleshooting, problem-solving, and debugging skills across distributed systems.</li><li>Excellent communication, collaboration, and documentation skills.</li><li>Demonstrated curiosity, ownership mindset, adaptability, and ability to guide product engineering teams.</li><li>Preferred Qualifications Experience designing, operating, or optimizing large-scale distributed database, messaging, search, or analytics platforms.</li><li>Experience operating or optimizing analytical databases and OLAP systems such as StarRocks, ClickHouse, Apache Doris, Druid, or Pinot.</li><li>Experience with streaming and real-time data platforms leveraging technologies such as Kafka, Flink, Spark, CDC, or similar ecosystems.</li><li>Exposure to Analytics, Data Engineering, AI/ML platforms, LLM-based applications, or AI infrastructure projects.</li><li>Experience using AI-assisted tooling or agents to improve operations, troubleshooting, documentation, or developer self-service.</li><li>Familiarity with modern data architectures and open table formats such as Apache Iceberg, Delta Lake, or Apache Hudi is a strong plus.</li><li>Experience with GitOps practices, CI/CD pipelines, and modern platform engineering methodologies.</li><li>Relevant certifications in Cloud Platforms, Kubernetes, Database Technologies, or Data Engineering are a plus.</li></ul><p></p></section>

<p><h4>Connect to your career at Deloitte</h4> <p>Deloitte, established globally in 1845, is the world’s largest and leading professional services firm, providing audit & assurance, tax & legal, consulting, and related services to public and private clients spanning multiple industries. Present in more than 150 countries, Deloitte is distinct in its ability to help clients solve their most complex problems, from strategy to implementation.</p> <p>Deloitte Innovation Hub (DIH) is a strategic initiative established to support our ambition to become the leading business transformation partner of choice for our clients and to expand and scale our delivery footprint across EMEA. With access to a scaled, diverse, highly skilled, motivated, and engaged workforce, DIH is delivering complex technical solutions for clients’ most complex business problems, across portfolios that include ‘Strategy & Transactions’, ‘Customer’, ‘Engineering, AI & Data’, ‘Enterprise, Technology & Performance’, and ‘Cyber’. DIH is aiming to become the destination for top talents in Egypt for a long, exciting career.</p> <p>We invest in outstanding people of diverse talents and backgrounds and empower them to achieve more than they could elsewhere. Our work combines advice with action and integrity. We believe that when our clients and society are stronger, so are we. Our organization has grown in scale and diversity, providing services across the region, with our shared culture remaining the same. We aim to help clients realize their ambitions, make a positive difference in society, and maximize the success of our people. This drive fuels the commitment and humanity that run deep through our every action.</p> <h4>Connect to your opportunity</h4> <ul> <li><strong>Problem-solving skills:</strong> Demonstrates the ability to identify and solve complex problems using a structured and logical approach.</li> <li><strong>Systems engineering:</strong> You should have experience in managing functional and non-functional requirements and have a deep understanding of systems engineering methodologies.</li> <li><strong>Stakeholder management:</strong> Demonstrates the ability to build and maintain positive relationships with stakeholders, and to effectively communicate technical concepts to non-technical audiences.</li> <li><strong>Organizational skills:</strong> Is highly organized and efficient and has a proven ability to manage multiple projects simultaneously.</li> <li><strong>Creativity and innovation:</strong> Are able to think creatively and come up with new solutions to problems.</li> <li><strong>Communication skills:</strong> Is able to communicate effectively with technical and non-technical audiences, both verbally and in writing.</li> </ul> <h4>Connect to your skills and professional experience</h4> <ul> <li>10+ years of experience in data engineering</li> <li><strong>Technical skills:</strong></li> <ul> <li>Cloud computing platforms: AWS / Azure / GCP</li> <li>Programming languages: Python / Java / Scala & Unix Shell scripting</li> <li>Data warehouse technologies: Redshift / Snowflake / Big Query</li> <li>Data lake technologies: Hadoop, Apache Beam, Spark, and Hive</li> <li>Orchestration: Airflow / Control-M / (Any orchestration tool)</li> <li>Machine learning frameworks: TensorFlow, PyTorch, and scikit-learn</li> </ul> </ul> <h4>Responsibilities</h4> <ul> <li>Lead a team of data engineers in the design, development, and implementation of data engineering solutions.</li> <li>Gather requirements from stakeholders and translate them into technical specifications.</li> <li>Design and implement data pipelines to collect, transform, and load data into data warehouses and data lakes.</li> <li>Maintain and optimize data systems to ensure high availability and performance.</li> <li>Work with other engineering teams to integrate data engineering solutions with other systems.</li> <li>Stay up to date on the latest data engineering technologies and trends.</li> </ul> <h4>Connect to your service line - Technology and Transformation</h4> <p>Distinctive thinking, deep expertise, and collaborative working. That’s what connects us. That’s what makes us Deloitte. If you want to help solve some of the biggest challenges around, join us. Together, we’ll make an impact that matters.</p> <h4>Personal independence</h4> <p>Regulation and controls are standard practice in our industry and Deloitte is no exception. These controls provide important legal protection for both you and the firm. We are subject to several audit regulations, one of which requires that certain colleagues abide by specific personal independence constraints. This can mean that you and your immediate family members are not permitted to hold certain financial interests (shares, funds, bonds etc.) with audit clients of the firm. The recruitment team will provide further detail as you progress through the recruitment process.</p> <h4>Connect to your industry</h4> <p>“What attracted me to Deloitte were the endless opportunities and the collective experience of other like-minded individuals. Deloitte’s clients include many of the world’s largest organisations; I wanted to be part of a team that made a difference that I could be proud of.” – Dan, Technology & Transformation</p> <h4>Our commitment to you</h4> <p>Making an impact is more than just what we do: it’s why we’re here. So we work hard to create an environment where you can experience a purpose you believe in, the freedom to be you, and the capacity to go further than ever before.</p> <p>We want you. The true you. Your own strengths, perspective, and personality. So, we’re nurturing a culture where everyone belongs, feels supported and heard, and is empowered to make a valuable, personal contribution. You can be sure we’ll take your wellbeing seriously, too. Because it’s only when you’re comfortable and at your best that you can make the kind of impact you, and we, live for.</p> <p>Your expertise is our capability, so we’ll make sure it never stops growing. Whether it’s from the complex work you do, or the people you collaborate with, you’ll learn every day. Through world-class development, you’ll gain invaluable technical and personal skills. Whatever your level, you’ll learn how to lead.</p> <h4>Connect to your next step</h4> <p>A career at Deloitte is an opportunity to develop in any direction you choose. Join us and you’ll experience a purpose you can believe in and an impact you can see. You’ll be free to bring your true self to work every day. And you’ll never stop growing, whatever your level.</p></p><p></p>

<p><h4>Connect to your career at Deloitte</h4> <p>Deloitte, established globally in 1845, is the world’s largest and leading professional services firm, providing audit & assurance, tax & legal, consulting, and related services to public and private clients spanning multiple industries. Present in more than 150 countries, Deloitte is distinct in its ability to help clients solve their most complex problems, from strategy to implementation.</p> <p>Deloitte Innovation Hub (DIH) is a strategic initiative established to support our ambition to become the leading business transformation partner of choice for our clients and to expand and scale our delivery footprint across EMEA. With access to a scaled, diverse, highly skilled, motivated, and engaged workforce, DIH is delivering complex technical solutions for clients’ most complex business problems, across portfolios that include ‘Strategy & Transactions’, ‘Customer’, ‘Engineering, AI & Data’, ‘Enterprise, Technology & Performance’, and ‘Cyber’. DIH is aiming to become the destination for top talents in Egypt for a long, exciting career.</p> <p>We invest in outstanding people of diverse talents and backgrounds and empower them to achieve more than they could elsewhere. Our work combines advice with action and integrity. We believe that when our clients and society are stronger, so are we. Our organization has grown in scale and diversity, providing services across the region, with our shared culture remaining the same. We aim to help clients realize their ambitions, make a positive difference in society, and maximize the success of our people. This drive fuels the commitment and humanity that run deep through our every action.</p> <h4>Connect to your opportunity</h4> <ul> <li><strong>Problem-solving skills:</strong> Demonstrates the ability to identify and solve complex problems using a structured and logical approach.</li> <li><strong>Systems engineering:</strong> You should have experience in managing functional and non-functional requirements and have a deep understanding of systems engineering methodologies.</li> <li><strong>Stakeholder management:</strong> Demonstrates the ability to build and maintain positive relationships with stakeholders, and to effectively communicate technical concepts to non-technical audiences.</li> <li><strong>Organizational skills:</strong> Is highly organized and efficient and has a proven ability to manage multiple projects simultaneously.</li> <li><strong>Creativity and innovation:</strong> Are able to think creatively and come up with new solutions to problems.</li> <li><strong>Communication skills:</strong> Is able to communicate effectively with technical and non-technical audiences, both verbally and in writing.</li> </ul> <h4>Connect to your skills and professional experience</h4> <ul> <li>10+ years of experience in data engineering</li> <li><strong>Technical skills:</strong></li> <ul> <li>Cloud computing platforms: AWS / Azure / GCP</li> <li>Programming languages: Python / Java / Scala & Unix Shell scripting</li> <li>Data warehouse technologies: Redshift / Snowflake / Big Query</li> <li>Data lake technologies: Hadoop, Apache Beam, Spark, and Hive</li> <li>Orchestration: Airflow / Control-M / (Any orchestration tool)</li> <li>Machine learning frameworks: TensorFlow, PyTorch, and scikit-learn</li> </ul> </ul> <h4>Responsibilities</h4> <ul> <li>Lead a team of data engineers in the design, development, and implementation of data engineering solutions.</li> <li>Gather requirements from stakeholders and translate them into technical specifications.</li> <li>Design and implement data pipelines to collect, transform, and load data into data warehouses and data lakes.</li> <li>Maintain and optimize data systems to ensure high availability and performance.</li> <li>Work with other engineering teams to integrate data engineering solutions with other systems.</li> <li>Stay up to date on the latest data engineering technologies and trends.</li> </ul> <h4>Connect to your service line - Technology and Transformation</h4> <p>Distinctive thinking, deep expertise, and collaborative working. That’s what connects us. That’s what makes us Deloitte. If you want to help solve some of the biggest challenges around, join us. Together, we’ll make an impact that matters.</p> <h4>Personal independence</h4> <p>Regulation and controls are standard practice in our industry and Deloitte is no exception. These controls provide important legal protection for both you and the firm. We are subject to several audit regulations, one of which requires that certain colleagues abide by specific personal independence constraints. This can mean that you and your immediate family members are not permitted to hold certain financial interests (shares, funds, bonds etc.) with audit clients of the firm. The recruitment team will provide further detail as you progress through the recruitment process.</p> <h4>Connect to your industry</h4> <p>“What attracted me to Deloitte were the endless opportunities and the collective experience of other like-minded individuals. Deloitte’s clients include many of the world’s largest organisations; I wanted to be part of a team that made a difference that I could be proud of.” – Dan, Technology & Transformation</p> <h4>Our commitment to you</h4> <p>Making an impact is more than just what we do: it’s why we’re here. So we work hard to create an environment where you can experience a purpose you believe in, the freedom to be you, and the capacity to go further than ever before.</p> <p>We want you. The true you. Your own strengths, perspective, and personality. So, we’re nurturing a culture where everyone belongs, feels supported and heard, and is empowered to make a valuable, personal contribution. You can be sure we’ll take your wellbeing seriously, too. Because it’s only when you’re comfortable and at your best that you can make the kind of impact you, and we, live for.</p> <p>Your expertise is our capability, so we’ll make sure it never stops growing. Whether it’s from the complex work you do, or the people you collaborate with, you’ll learn every day. Through world-class development, you’ll gain invaluable technical and personal skills. Whatever your level, you’ll learn how to lead.</p> <h4>Connect to your next step</h4> <p>A career at Deloitte is an opportunity to develop in any direction you choose. Join us and you’ll experience a purpose you can believe in and an impact you can see. You’ll be free to bring your true self to work every day. And you’ll never stop growing, whatever your level.</p></p><p></p>