Data Entry Jobs in Egypt

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>Lead the design and implementation of enterprise Data Management frameworks, governance models, policies, standards, and operating procedures. The consultant will work closely with business and IT stakeholders to improve data quality, establish data ownership, ensure regulatory compliance, and maximize the business value of organizational data assets.</p><br><p><strong>Key Responsibilities</strong></p><br><ul><li>Lead enterprise Data Management and Data Governance initiatives. </li><li>Develop Data Governance Frameworks, Policies, Standards, and Procedures. </li><li>Define data ownership, stewardship, and accountability models. </li><li>Establish Data Quality frameworks, KPIs, and monitoring processes. </li><li>Design Metadata Management and Business Glossary structures. </li><li>Develop Master Data Management (MDM) strategies. </li><li>Support Data Catalog implementation and governance. </li><li>Define Data Lifecycle Management processes. </li><li>Develop Data Classification and Data Retention policies. </li><li>Assess current-state data maturity and recommend improvements. </li><li>Conduct data governance workshops with business stakeholders. </li><li>Support implementation of governance tools and platforms. </li><li>Ensure compliance with local and international regulations. </li><li>Prepare executive reports, dashboards, and governance metrics. </li><li>Mentor Data Management Specialists. </li></ul> </div>

<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>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>Talent 360 is looking for a " Senior Data Fabric &amp; AI Engineer" to join their growing team! If you're passionate about artificial intelligence, modern data platforms, and building scalable data solutions, this is an excellent opportunity to advance your career in a dynamic and collaborative environment. As a Senior AI &amp; Data Fabric Engineer , you will be responsible for designing, developing, and optimizing AI-powered data solutions and Data Fabric architectures. You will build and maintain scalable data pipelines, integrate AI and machine learning capabilities into enterprise data platforms, and collaborate with cross-functional teams to deliver secure, high-performing, and data-driven solutions that support business and analytics initiatives.</p><p>Lead technical discovery and data maturity assessments with enterprise customers across Saudi Arabia and Egypt</p><p>Design and present data platform architectures using modern tools (Microsoft Fabric, Azure Data Services, OpenMetadata, SQLMesh)</p><p>Create compelling business cases that connect data governance and AI capabilities to measurable business outcomes</p><p>Develop technical proposals, solution architectures, and pricing models for data and AI engagements</p><p>Deliver demonstrations of AI agent workflows, agentic automation, and conversational data access patterns</p><p>Support Microsoft co-sell motions for Azure AI, Microsoft Fabric, and Copilot-related opportunities</p><p>Collaborate with the Product Developer to align presales demonstrations with current product capabilities</p><p>Contribute to thought leadership content: whitepapers, case studies, and technical blog posts</p><p>Track competitive landscape across data governance and AI platforms (Informatica, Collibra, Databricks, Coalesce)</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>3-5 years of experience in data engineering, data architecture, or AI/ML presales</li><li>Understanding of modern data stack: data warehouses, data lakes, ETL/ELT pipelines, data governance</li><li>Familier with data services (Azure Data Factory, Synapse, Microsoft Fabric, Purview or similar )</li><li>Familiarity with AI/ML concepts and practical applications in enterprise settings</li><li>Experience creating data architecture diagrams and technical documentation</li><li>Excellent presentation and storytelling skills, capable of translating technical concepts for executive audiences</li><li>English and Arabic fluency</li></ul><p></p></section>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and design appropriate solutions. Work closely with IT and infrastructure teams to deploy and maintain data storage and processing systems, including databases, data warehouses, and cloud infrastructure. Design, build, and maintain robust, scalable data pipelines to ingest, process, and transform data from various sources, including internal databases and external APIs. Optimize data pipelines for performance, scalability, and reliability, ensuring timely and accurate delivery of data. Implement data validation and quality checks to identify and rectify any issues in data pipelines, ensuring data integrity. Explore and evaluate new technologies, tools, and frameworks to improve data engineering processes and capabilities. Perform data modeling and schema design to support analytical and reporting requirements. Design and build data marts and business layers to facilitate efficient data access and analysis.</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p>Bachelor s degree in Computer Science, Information Systems, or other related technical field or equivalent work. Proven experience as a Data engineer or similar role, with at least 4 years of experience. Advanced SQL knowledge/experience - complex queries and query optimization. Proficiency in programming languages such as Python. Experienced in the development of data warehouses and proficient in data modeling. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform. Experience in building data streams using technologies such as Kafka, Flink, or Spark Streaming is considered a plus. Strong problem-solving skills and attention to detail. The ability and willingness to learn new technologies on the job. Self driven, highly motivated, fast learner, ambitious and creative.</p><p></p></section>

<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>

<p><strong>Key Responsibilities:</strong></p><ol><li><p>Design, build, and maintain reliable <strong>ETL/ELT data pipelines</strong> from multiple data sources into the Data Warehouse and analytics platforms.</p></li><li><p>Build, enhance, and optimize <strong>data models, semantic models, and DWH structures</strong> to support reporting, analytics, and business intelligence needs.</p></li><li><p>Transform, cleanse, and enrich raw data into trusted datasets that enable meaningful insights, KPIs, dashboards, and analytics reports.</p></li><li><p>Support data visualization and BI solutions using <strong>Power BI</strong> and <strong>Microsoft Fabric</strong>.</p></li></ol><p></p><p><strong>Requirements</strong></p><ul><li><p>Strong knowledge of <strong>Database Modeling, Data Warehousing, and DWH concepts</strong>.</p></li><li><p>Hands-on experience with <strong>MS SQL</strong>.</p></li><li><p>Experience in <strong>ETL/ELT tools</strong> such as SSIS, dbt, Airflow, or similar.</p></li><li><p>Data visualization and dashboard development using <strong>Power BI</strong>.</p></li><li><p>Data analytics and Business Intelligence using <strong>Microsoft Fabric</strong>.</p></li><li><p>Familiarity with <strong>DevOps practices</strong>, version control, and deployment pipelines.</p></li></ul><p></p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>About Valleysoft Valleysoft is an IT services provider delivering enterprise technology, application development, process management, and IT support solutions to clients worldwide.<br> Operating across the Information Technology and Services sector, the company partners with organizations on complex digital transformation initiatives and business-critical systems that support day-to-day operations and long-term growth.<br> Job Summary The Data Engineer (Data Integration) will be responsible for designing, developing, and maintaining enterprise data integration solutions that enable the efficient movement of data from operational and external source systems into the business intelligence and analytics environment.<br> The role requires strong expertise in ETL development, data integration, data transformation, and data quality using enterprise integration tools such as Informatica, IBM DataStage, or Ab Initio.<br> This position is an on-site role based at the Administrative Control Authority (ACA) in the New Administrative Capital.<br> Key Responsibilities Design, develop, and maintain enterprise data integration and ETL solutions.<br> Build Extract, Transform, and Load (ETL) processes to integrate data from multiple operational and external source systems.<br> Develop data mappings, transformation logic, workflows, and reusable integration components.<br> Ensure data quality, integrity, consistency, and completeness throughout the data integration lifecycle.<br> Monitor, troubleshoot, and optimize ETL jobs for performance, scalability, and reliability.<br> Collaborate with business analysts, data architects, BI developers, and application teams to understand data requirements.<br> Support data migration, reconciliation, validation, and production deployments.<br> Participate in data modeling, data profiling, and metadata management activities.<br> Develop and maintain technical documentation, ETL specifications, and operational procedures.<br> Support production issues, root cause analysis, and continuous improvement initiatives.<br> Requirements Bachelor's degree in Computer Science, Information Technology, Information Systems, Engineering, or a related field.<br> Relevant certifications in Informatica, IBM DataStage, or other data integration technologies are a plus.<br> 6+ years of experience in Data Engineering, Data Integration, or ETL Development.<br> Proven experience delivering enterprise-scale data integration projects.<br> Hands-on experience with at least one leading ETL tool such as Informatica PowerCenter, IBM DataStage, or Ab Initio.<br> Experience working with large-scale enterprise data warehouse or business intelligence environments.<br> Must-Have Requirements Min 3 years of experience in Data Engineering or Data Integration.<br> Strong hands-on experience with Informatica PowerCenter, IBM DataStage, or Ab Initio.<br> Strong knowledge of ETL design, development, and optimization.<br> Experience with SQL and relational database management systems such as Oracle, SQL Server, or PostgreSQL.<br> Experience working with Data Warehousing and Business Intelligence environments.<br> Strong understanding of data integration architecture, data mapping, transformation, and data validation.<br> Experience with performance tuning and troubleshooting ETL workflows.<br> Knowledge of data quality, data governance, and metadata management principles.<br> Excellent analytical, problem-solving, and communication skills.<br> Ability to work effectively in a collaborative, cross-functional environment.<br> Fluent in English, both written and spoken.<br> Good-to-Have Requirements Experience with cloud-based data integration platforms (Azure, AWS, or Google Cloud).<br> Familiarity with Big Data technologies such as Hadoop or Spark.<br> Experience with Python or Shell scripting for ETL automation.<br> Knowledge of CI/CD pipelines and DevOps practices for data engineering.<br> Experience in government, financial services, or large enterprise environments.<br> Experience with data governance frameworks and enterprise data management.<br></span> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>As <strong>Sr Data Engineer</strong> you will drive the design, deployment, and continuous optimization of scalable data pipelines that ingest and process a wide variety of structured and unstructured data sources into Mondia’s AWS-based data warehouse and data lake.</p><br><p>Implement and maintain reliable data ingestion, transformation, orchestration, monitoring, and CI/CD capabilities across the data platform. Promote operational excellence through automation, GitLab pipelines, Infrastructure as Code, observability, and robust engineering standards.</p><br><p>Ensure that high-quality, secure, and well-governed data is available for reporting, advanced analytics, and AI- and machine-learning-enabled use cases across Mondia’s business entities.</p><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Talent 360 is looking for a " Senior Data Fabric &amp; AI Engineer" to join their growing team!<br> If you're passionate about artificial intelligence, modern data platforms, and building scalable data solutions, this is an excellent opportunity to advance your career in a dynamic and collaborative environment.<br> As a Senior AI &amp; Data Fabric Engineer , you will be responsible for designing, developing, and optimizing AI-powered data solutions and Data Fabric architectures.<br> You will build and maintain scalable data pipelines, integrate AI and machine learning capabilities into enterprise data platforms, and collaborate with cross-functional teams to deliver secure, high-performing, and data-driven solutions that support business and analytics initiatives.<br> Company Industry : Information Technology Services Location: Maadi - Cairo Working Hours: 9:00 AM to 5:00 PM.<br> Working Days: From Sun to Thu.<br> Benefits: Attractive salary - Social &amp; Medical insurance - Friendly Environment - Learning &amp; Development Opportunities - Other benefits Apply now to drive innovation and growth with our dynamic team!<br> Lead technical discovery and data maturity assessments with enterprise customers across Saudi Arabia and Egypt Design and present data platform architectures using modern tools (Microsoft Fabric, Azure Data Services, OpenMetadata, SQLMesh) Create compelling business cases that connect data governance and AI capabilities to measurable business outcomes Develop technical proposals, solution architectures, and pricing models for data and AI engagements Deliver demonstrations of AI agent workflows, agentic automation, and conversational data access patterns Support Microsoft co-sell motions for Azure AI, Microsoft Fabric, and Copilot-related opportunities Collaborate with the Product Developer to align presales demonstrations with current product capabilities Contribute to thought leadership content: whitepapers, case studies, and technical blog posts Track competitive landscape across data governance and AI platforms (Informatica, Collibra, Databricks, Coalesce) Job Qualifications: 3-5 years of experience in data engineering, data architecture, or AI/ML presales Understanding of modern data stack: data warehouses, data lakes, ETL/ELT pipelines, data governance Familier with data services (Azure Data Factory, Synapse, Microsoft Fabric, Purview or similar ) Familiarity with AI/ML concepts and practical applications in enterprise settings Experience creating data architecture diagrams and technical documentation Excellent presentation and storytelling skills, capable of translating technical concepts for executive audiences English and Arabic fluency</span> </div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>As a Data Analyst at Prepit, you will be responsible for analyzing data, building and maintaining ETL processes, ensuring data quality, and delivering insights that drive product and business decisions. You'll collaborate closely with Product, Engineering, and Business teams to develop scalable reporting solutions and support a data-driven culture.</p><p>Key Responsibilities</p><ul><li>Collect, clean, transform, and analyze data from multiple sources.</li><li>Design, develop, and maintain ETL/ELT pipelines to ensure reliable and timely data availability.</li><li>Write efficient SQL queries to extract, validate, and analyze data.</li><li>Build and maintain dashboards and reports using Metabase.</li><li>Partner with Product, Engineering, and Business teams to define KPIs and reporting requirements.</li><li>Monitor data quality and implement validation checks to ensure data accuracy.</li><li>Perform ad hoc analyses to identify trends, opportunities, and business insights.</li><li>Support data modeling and optimize datasets for reporting and analytics.</li><li>Document data sources, ETL processes, and reporting logic.</li><li>Continuously improve data workflows through automation and process optimization.</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 Science, Information Systems, Statistics, Engineering, or a related field.</li><li>2 years of experience as a Data Analyst or in a similar role.</li><li>Strong proficiency in SQL.</li><li>Hands-on experience designing and maintaining ETL/ELT processes.</li><li>Experience working with relational databases (PostgreSQL, MySQL, or similar).</li><li>Experience creating dashboards and reports using Metabase.</li><li>Good understanding of data modeling and data warehousing concepts.</li><li>Experience with Python (Pandas) for data analysis or automation is a plus.</li><li>Familiarity with cloud platforms and modern data architectures is an advantage.</li><li>Excellent analytical, problem-solving, and communication skills.</li><li>Ability to work independently in a fast-paced startup environment.</li></ul><p></p></section>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>As Sr Data Engineer you will drive the design, deployment, and continuous optimization of scalable data pipelines that ingest and process a wide variety of structured and unstructured data sources into Mondia’s AWS-based data warehouse and data lake.<br> Implement and maintain reliable data ingestion, transformation, orchestration, monitoring, and CI/CD capabilities across the data platform.<br> Promote operational excellence through automation, GitLab pipelines, Infrastructure as Code, observability, and robust engineering standards.<br> Ensure that high-quality, secure, and well-governed data is available for reporting, advanced analytics, and AI- and machine-learning-enabled use cases across Mondia’s business entities.<br> Social insurance Health insurance for employee and family The company will contribute up to EUR 25 per month towards staff perks Benefit from our performance-based bonus scheme , in line with company policy.<br> EUR equivalent salaries paid in EGP Responsibilities: Collaborate with data engineers, data analysts, product and web analytics teams, software engineers, and business stakeholders in a collaborative and iterative environment.<br> Provide technical guidance and contribute to the definition of data architecture, engineering standards, and reusable solutions across Mondia’s data ecosystem.<br> Design and maintain the data foundations required to deliver reliable internal data products, including well-defined datasets, data sources, dashboards, reports, and analytical solutions.<br> Contribute as a senior member of the team to the reliable operation, performance, scalability, and cost efficiency of Mondia’s AWS-based data platform, including Amazon Redshift, Athena, AWS Glue, Amazon S3, Step Functions, Lambda, EC2, and related AWS services.<br> Design, build, test, deploy, monitor, and maintain end-to-end data pipelines and data management solutions using AWS Glue, Python, SQL, Spark/PySpark, and similar cloud-based ETL and data-processing technologies.<br> Design and implement data models, schemas, tables, and storage structures across Amazon Redshift, Amazon S3, and the wider AWS data platform.<br> Design and maintain orchestration patterns, workflows, event-driven components, and scheduling solutions using AWS Step Functions, AWS Glue Workflows, Amazon EventBridge, AWS Lambda, and similar technologies.<br> Promote operational excellence through automation, GitLab CI/CD, Infrastructure as Code, observability, testing, documentation, and consistent engineering practices.<br> Define, implement, and continuously improve automated data-quality and reliability controls, including checks for completeness, accuracy, consistency, validity, duplication, freshness, and reconciliation.<br> Maintain appropriate data lineage, metadata, technical documentation, and ownership information to improve transparency, trust, and maintainability.<br> Use appropriate programming languages, integration patterns, and engineering tools to connect systems and deliver reliable data solutions.<br> Evaluate technologies based on the use case and adapt as platforms and requirements evolve.<br> Use approved AI technologies and AI-assisted development tools as part of daily engineering activities to improve productivity, code quality, testing, documentation, troubleshooting, and solution design.<br> Identify opportunities to integrate AI capabilities into data products where they provide measurable business or operational value.<br> Communicate technical concepts, results, risks, and recommendations clearly to both technical and non-technical stakeholders across all levels of the organization.<br> Document architectures, data flows, design decisions, operational procedures, and technical standards, while contributing constructively to technical discussions and engineering decisions.<br> Comply with Mondia’s policies, procedures, security requirements, and data-governance standards, while supporting the company’s mission, vision, and values.<br> Perform other reasonable job-related duties and responsibilities as assigned by the direct manager.<br> Bachelor’s degree in Computer Science/Engineering or Statistics.<br> Skills &amp; Experience: +3 years of professional experience in Data Engineering or Data Warehousing with an integrative perspective, from management to operations involvement and hands-on experience with cloud architecture and cloud technologies such as AWS, Azure or Google Cloud Platform GCP.<br> Strong proficiency in Python and SQL; experience with Scala, Java, or Bash/Shell scripting is an advantage.<br> Solid experience with AWS data services, particularly Amazon Redshift, S3, Glue, Athena, Lambda, Step Functions, and EventBridge.<br> Strong understanding of data warehouse, data lake, ETL/ELT, data modelling, and cloud data architecture concepts.<br> Experience building and operating scalable data pipelines using AWS Glue, Spark/PySpark, or similar technologies.<br> Good understanding of cloud security, identity and access management, data protection, monitoring, and logging.<br> Experience with APIs, microservices, and event-driven integration patterns.<br> Working knowledge of GitLab CI/CD, automation, Infrastructure as Code, and modern software engineering practices.<br> Experience using AI-assisted development tools to improve engineering productivity and quality.<br> Very good written and spoken English, with strong technical documentation and communication skills.<br></span> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>About us Infomineo is a pioneering global AI-enhanced research company that transforms how businesses access, analyze, and act on critical intelligence.<br> We’ve evolved from traditional business research outsourcing to become the strategic partner that combines cutting-edge artificial intelligence with deep human expertise.<br> We offer 3 services to our global clients (leading consulting companies, Fortune 500 companies, and government entities): AI and Data Advisory, Next-Gen Insights and Resource Scaling.<br> This is made possible by relying on 3 pillars of excellence: 350+ industry experts spread across 5 offices (Cairo, Casablanca, Mexico City, Dubai, Barcelona).<br> Our proprietary AI orchestrator.<br> Extensive knowledge assets combining 500,000+ delivered case studies and database subscriptions.<br> Ready to kick start your career with us?<br> About this role This role will give you the opportunity to work on high added value data governance and data quality projects, building robust data management frameworks for our clients within a growing service company.<br> As our Data Governance Specialist, you will help clients take control of their data assets — defining policies, enforcing quality standards, managing metadata, and deploying governance tooling.<br> You will collaborate closely with data engineers, analysts, and client stakeholders to embed governance practices across the full data lifecycle.<br> What will you do?<br> Design, implement, and operationalize data governance frameworks across client engagements, covering the following areas: DATA GOVERNANCE &amp; POLICY Define and implement data governance frameworks, policies, and standards tailored to client environments.<br> Establish data ownership, stewardship models, and accountability structures across business and technical teams.<br> Develop and maintain data dictionaries, business glossaries, and classification taxonomies.<br> Ensure compliance with data regulations and internal data management policies (GDPR, BCBS 239, etc.<br>). DATA QUALITY &amp; LINEAGE Design and implement data quality rules, profiling routines, and monitoring dashboards.<br> Investigate and remediate data quality issues across structured and unstructured data sources.<br> Map and document end-to-end data lineage to support auditability and impact analysis.<br> Define and track data quality KPIs and SLAs in collaboration with data owners.<br> METADATA &amp; CATALOGUING Deploy and administer data catalog and metadata management tools (e.<br>g. Informatica, Collibra, Alation, Microsoft Purview).<br> Enrich metadata assets with business context, ownership, sensitivity classification, and usage information.<br> Drive adoption of the data catalog across business and technical teams.<br> TOOLING &amp; INTEGRATION Configure and operate data governance platforms, primarily Informatica (IDMC, Axon, EDC, DQ) and equivalent tools.<br> Integrate governance tooling with existing data pipelines, warehouses, and BI environments.<br> Automate data quality checks and governance workflows within ETL/ELT pipelines.<br> OTHER Provide internal training and knowledge-sharing sessions on data governance best practices.<br> Support the Team Lead/Manager on client relationships, business development, and internal projects.<br> Who are you?<br> EDUCATION &amp; PROFESSIONAL EXPERIENCE Master’s degree in a relevant field such as Computer Science, Information Systems, Data Management, Statistics, or Applied Mathematics.<br> Full proficiency in English + 1 additional language (French, Arabic, Spanish, German.<br>..). 3 to 6 years of experience in data governance, data management, or data engineering with a strong governance focus.<br> Experience working in a consulting, financial services, or multi-client environment is a plus.<br> TECHNICAL SKILLS DATA GOVERNANCE TOOLS Proven hands-on experience with Informatica (IDMC / Intelligent Data Management Cloud, Axon Data Governance, Enterprise Data Catalog, Data Quality).<br> Experience with other governance and cataloguing platforms such as Collibra, Alation, Ataccama, or Microsoft Purview.<br> Familiarity with data quality tools: Great Expectations, Monte Carlo, Soda, or equivalent.<br> DATA ENGINEERING &amp; QUERYING Solid experience with SQL for data profiling, querying, and quality rule implementation across relational databases and data warehouses (Snowflake, BigQuery, Synapse, Redshift).<br> Experience in Python for automating data quality checks, metadata extraction, and governance workflows.<br> Understanding of ETL/ELT pipelines and ability to embed governance controls within them (dbt, Airflow, Informatica PowerCenter/IDMC).<br> DATA ARCHITECTURE &amp; PLATFORMS Good understanding of data platform architectures: data lake, lakehouse, and data warehouse environments.<br> Familiarity with cloud platforms and their native governance services: Azure Purview, AWS Glue Data Catalog, Google Dataplex.<br> Understanding of data modelling concepts and their impact on governance (dimensional modelling, data vault, etc.<br>). STANDARDS &amp; COMPLIANCE Knowledge of data governance frameworks and standards: DAMA-DMBOK, BCBS 239, GDPR, ISO 8000.<br> Experience defining and applying data classification schemes (sensitivity labels, PII tagging, retention policies).<br> Exposure to master data management (MDM) concepts and tools is a plus.<br> INTERPERSONAL SKILLS Ability to engage and influence both technical teams and business stakeholders on data governance topics.<br> Strong analytical mindset with the ability to diagnose data quality issues and translate them into actionable remediation plans.<br> Good communication skills with the ability to document governance frameworks clearly and present findings to senior audiences.<br> Detail-oriented, rigorous, and comfortable working across multiple client contexts simultaneously.<br> What we offer A competitive salary.<br> A great working environment.<br> A steep learning curve with interesting and diverse topics to work on.<br> A healthy work-life balance.<br> Health insurance benefits.<br> Equal opportunity employer Infomineo is an equal opportunity employer, we prohibit any sort of discrimination (based on color, race, sex, sexual orientation, religion, national origin or any other attributes) in all aspects of employment (recruiting, hiring, wages and salary, promotions, benefits, training and job termination).<br> If you believe you match our requirements and values, we would be happy to hear from you.<br> Visit our website to know more about us, our services and company culture.<br></span> </div>

Knowledge & Technical Skills Required Have the skills necessary to create and maintain a data management framework that establishes roles and responsibilities for data governance and decision making to meet the enterprise's data objectives and goals. Responsible for loading and validating data into the data management framework Responsible for building end to end lineage for all data assets within the data management framework Investigate data quality related issues and able to identify root causes and build solution plan Investigate data management platform related issues and optimize performance Have the skills necessary to understand organization data & current analytical landscape complex data models Database expert and able to perform environment assessment & optimize performance up to max extend within available resources Knowledge of industry leading data quality and data protection management practices Knowledge of data governance practices, business and technology issues related to management of enterprise information assets and approaches related to data protection Knowledge of data related government regulatory requirements and emerging trends and issues Understand the overall core concepts for analytics and data management Monitors usage of the data management platform to identify potential capacity overloads and bottlenecks Collaborates with different stakeholders to identify, define, develop and implement new requirements Participates in writing and reviewing functional specifications and design reviews Able to design and development of the ETL environment, processes, programs, and scripts to acquire data from source systems and inject to analytical landscape. Provides support for technical issues and ensuring system availability Support the analysis and documentation of data capture to execute upon reporting requirements to meet business needs Remains current on data platform technologies, testing industry trends and best practices Ownership of projects and responsible for deliverables Ability to translate business requirements into technical solutions Strong interpersonal and relationship building skills, conducive to team development, work under own initiative. Ability to prioritize tasks and work concurrently on multiple tasks. Self-starter with "can-do" attitude, a must in a fast-paced business and technical environment Good to have advanced statistical and machine learning knowledge to discover similar data and subsets of data, helping users find the most relevant and trusted data the business needs. Additional responsibilities may be assigned<br>MUST HAVE10+ years Informatica Suite experience mainly in data management implementation (Should be well versed to use Informatica Enterprise Data Catalog, Axon Data Governance and Informatica Data Quality or any similar capability )10+ years of experience in software development10+ years of database experience and writing shell scripts<br>Certification specifications if any Educational Qualifications Bachelors or master’s in computer engineering, Computer Science, MIS, or Information Management

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><strong>Remote Data Analyst</strong><br>Colaval<br><strong>Job Overview</strong><br>Colaval, a leading global manufacturer of high-quality control valves and water treatment solutions, is seeking a diligent and analytical <strong>Remote Data Analyst</strong> to join our team on a <strong>full-time</strong> basis. Based remotely within the <strong>United States</strong>, the successful candidate will play a crucial role in transforming data into actionable insights that will drive our business forward. You will support our commitment to providing professional technical knowledge and effective solutions by analysing complex datasets related to our industrial, commercial, and residential sectors. This is an excellent opportunity for a data-driven individual to contribute to a company focused on innovation and sustainable development.<br><strong>Responsibilities</strong><br>As a Data Analyst, you will be responsible for:<br></p><br><br><ul><li>Collecting, interpreting, and analysing data from various sources, including sales, manufacturing, and supply chain systems.</li><li>Developing and implementing data analyses, data collection systems, and other strategies that optimise statistical efficiency and quality.</li><li>Identifying, analysing, and interpreting trends or patterns in complex data sets to provide clear business insights.</li><li>Creating and maintaining dashboards and reports to communicate key business metrics and findings to stakeholders.</li><li>Collaborating with management and various departments to identify and prioritise business and information needs.</li><li>Providing data-driven recommendations to improve operational efficiency and support strategic decision-making.</li><li>Ensuring data accuracy and integrity across all reporting platforms.</li></ul><p><strong>Qualifications</strong><br>The ideal candidate will possess the following:<br></p><br><br><ul><li>Proven experience working as a Data Analyst or Business Data Analyst.</li><li>Strong technical expertise regarding data models, database design, data mining, and segmentation techniques.</li><li>Proficiency in SQL and a strong knowledge of reporting and data visualisation tools such as Power BI or Tableau.</li><li>Excellent knowledge of statistics and experience using statistical packages for analysing datasets (e.g., Excel, SPSS, SAS).</li><li>A degree in Mathematics, Economics, Computer Science, Information Management, Statistics, or a related field.</li><li>Exceptional analytical and problem-solving skills with a high level of attention to detail.</li><li>Strong written and verbal communication skills, with the ability to present complex information clearly and concisely.</li><li>Experience within the manufacturing or industrial sector would be highly advantageous.</li></ul><p><br><strong>Benefits</strong><br>What We Offer:<br></p><br><br><ul><li>A competitive annual salary of <strong>$45 - $55 USD</strong>.</li><li>A fully remote working arrangement, providing flexibility and work-life balance.</li><li>The opportunity to be part of an innovative, global company with a focus on sustainability.</li><li>A collaborative and supportive team environment.</li><li>Opportunities for professional growth and development.</li></ul><br> <br><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> Introduction <br> <p>A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.</p><br><br> <br> <br> Your role and responsibilities <br> <p>As a Data Engineer specializing in Data Integration, you will design and build solutions to transfer data from operational and external environments to the business intelligence environment. You will utilize specialized tools to create and implement Extract, Transform, and Load (ETL) processes, ensuring the seamless flow of data throughout the business intelligence solution's lifecycle.</p><br><br><p>Your primary responsibilities will include:</p><br><br><p>* <strong>Design Data Integration Solutions:</strong> Create solutions to transfer data from operational and external environments to the business intelligence environment, utilizing tools such as Informatica, Ab Initio software, and DataStage.</p><br><br><p>* <strong>Implement ETL Processes:</strong> Develop and implement Extract, Transform, and Load (ETL) processes to ensure the seamless flow of data throughout the business intelligence solution's lifecycle.</p><br><br><p>* <strong>Utilize Specialized Tools:</strong> Apply knowledge of Informatica, Ab Initio software, and DataStage to design and build data integration solutions.</p><br><br><p>* <strong>Ensure Seamless Data Flow:</strong> Ensure the smooth flow of data throughout the business intelligence solution's lifecycle by creating and implementing effective ETL processes.</p><br><br><p>* <strong>Support Business Intelligence:</strong> Support the business intelligence environment by designing and building solutions to transfer data from operational and external environments.</p><br><br> <br> <br> Required education <br> Bachelor's Degree <br> <br> Required technical and professional expertise <br> <p>* <strong>Exposure to Data Integration Tools:</strong> Familiarity with tools such as Informatica, Ab Initio software, and DataStage (formerly Ascential) - IBM's WebSphere Data Integration Suite.</p><br><br><p>* <strong>ETL Process Implementation:</strong> Experience working with Extract, Transform, and Load (ETL) processes to ensure the seamless flow of data throughout the business intelligence solution's lifecycle.</p><br><br><p>* <strong>Data Solution Design:</strong> Exposure to designing solutions to transfer data from operational and external environments to the business intelligence environment.</p><br><br><p>* <strong>Business Intelligence Environment:</strong> Experience working within a business intelligence environment, supporting data integration solutions.</p><br><br><p>* <strong>Data Flow Management:</strong> Exposure to ensuring the smooth flow of data throughout the business intelligence solution's lifecycle.</p><br><br> <br> <br> Preferred technical and professional experience <br> <p>* <strong>Additional Data Integration Tools:</strong> Exposure to other data integration tools beyond Informatica, Ab Initio software, and DataStage can be beneficial in this role.</p><br><br><p>* <strong>Advanced ETL Techniques:</strong> Experience working with advanced ETL techniques and methodologies can enhance the ability to design and implement efficient data integration solutions.</p><br><br><p>* <strong>Business Intelligence Platforms:</strong> Familiarity with various business intelligence platforms can support the development of effective data integration solutions.</p><br><br> <br> <br> <br> <br> <br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Develop and implement the data engineering strategy in line with our business objectives and industry best practices Lead, mentor, and grow a team of data engineers, fostering a culture of innovation, collaboration, and continuous improvement Collaborate with the Data Architect to design, build, and optimize data infrastructure, ensuring it is scalable, secure, and performant Work closely with other engineering managers to ensure seamless data integration and accessibility for analytics and business intelligence initiatives Establish and enforce data engineering standards, guidelines, and best practices across the organization Identify, evaluate, and implement new data technologies and tools to enhance the capabilities of the data team Collaborate with cross-functional teams to identify data requirements and support data-driven projects Monitor and maintain the health and performance of mylo's data ecosystem, proactively identifying and addressing any issues Office environment: When you come to our b_labs office, you'll find creative workspaces and an open design to foster collaboration between teams.<br> Flexibility: You know best whether you want to work from home or in the office.<br> Equipment: From "Day 1" you will receive all the equipment you need be successful at work.<br> Bachelor's or Master's degree in Computer Science, Engineering, or a related field Minimum of 8 years of experience in data engineering, with at least 3 years in a leadership role Strong knowledge of data science tools, technologies, and best practices, including data warehousing, ETL, and data pipelines Proficiency in programming languages such as Python, Java, or Scala Experience with big data technologies such as Hadoop, Spark, and Kafka Familiarity with cloud-based data solutions (AWS, Azure, or Google Cloud) Exceptional problem-solving, communication, and leadership skills Ability to collaborate effectively with cross-functional teams and stakeholders</span> </div>

<p><h4>Join us<\/h4>\n<p>At Vodafone, weu2019re not just shaping the future of connectivity for our customers u2013 weu2019re shaping the future for everyone who joins our team. When you work with us, youu2019re 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>\n\n<h4>Role purpose<\/h4>\n<p>To design a unified, scalable, and secure data blueprint in conjunction with the tech group to integrate scattered network and business data. This role ensures that all data projects align with the business vision while maintaining a unified standard across all departments to avoid data silos.<\/p>\n\n<h4>Role profile<\/h4>\n<p><strong>Technology stack ownership and alignment with data group technology:<\/strong> Lead the evaluation and selection of all data tools and ensure group approval for these tools (e.g., choosing the data virtualization tools, choosing the cloud provider, or the data lake technology). Also responsible for reporting to the group architecture maturity index and initiating any project to meet it.<\/p>\n<p><strong>Enterprise data transformation:<\/strong> Assess current and planned architecture and identify gaps towards trustworthy data and work on high-level design for these projects to ensure engagement of business and governance u2013 during the project, the principal architect will be responsible for ensuring that objectives and KPIs are achieved.<\/p>\n<p><strong>Data infrastructure readiness for AI:<\/strong> Preparing the data foundation so that internal data scientists can safely use data in their models to learn. If any gaps are discovered, a roadmap should be put in place to close them.<\/p>\n<p><strong>Architectural enablement for \"Intelligent Data Apps\":<\/strong> The architect must ensure the data infrastructure perfectly supports intelligent data software products that add more analytical insights for business (inbound and outbound data flow) and future-proof visualization tools.<\/p>\n<p><strong>Business alignment, governance, and lifecycle management:<\/strong> The architect ensures the technology roadmap serves business demand and maintains the long-term health of the data ecosystem.<\/p>\n\n<h4>Responsibilities<\/h4>\n<p><strong>Technology stack ownership and alignment with data group technology:<\/strong><\/p>\n<ul>\n<li>Negotiate with group architecture on yearly plan and budget.<\/li>\n<li>Responsible for evaluating SOA and identifying gaps to be studied and budgeted for implementation.<\/li>\n<li>Cross-domain modeling alignment: Collaborate with group architecture to review data attributes across complex domains (e.g., network core, BSS\/OSS, retail transactions), ensuring schemas are optimized for high-performance processing inside intelligent data apps.<\/li>\n<\/ul>\n\n<p><strong>Enterprise data transformation<\/strong><\/p>\n<ul>\n<li>Assess current and planned architecture and identify gaps towards trustworthy data and work on these projects until they are transferred from a gap to a project with an initial study document including high-level design, KPIs, and budget u2013 during the project, act as principal architect responsible for low-level design and ensuring that objectives and KPIs are achieved.<\/li>\n<li>Introduce advanced data virtualization strategies (e.g., Trino, Denodo) to sit on top of all data sources, allowing real-time, low-latency querying without moving raw data unnecessarily.<\/li>\n<li>Data lakehouse evolution: Serve as the principal architect for migrating the companyu2019s legacy big data (Hadoop\/On-Prem) estate to a modern, cloud\/hybrid data lakehouse environment (e.g., Databricks, Snowflake, Delta Lake). Design the multi-phase migration roadmap, focusing on decoupling compute\/storage separation and concurrency standards.<\/li>\n<li>Data governance integration: Architect automated hooks within the lakehouse migration so that data metadata, schemas, and lineage are automatically captured by the governance framework at ingestion.<\/li>\n<li>DaaS evolution: Review and expand the existing DaaS (API) infrastructure. Document the blueprint for the underlying current\/new architecture that exposes data assets via secure, high-speed APIs, allowing developers to query enterprise data.<\/li>\n<\/ul>\n\n<p><strong>Data infrastructure readiness for AI<\/strong><\/p>\n<ul>\n<li>Prepare the data foundation so that internal data scientists and external enterprise AI clients can safely consume the telecom data core.<\/li>\n<li>Semantic layering for GenAI (\"Chat with Data\"): Architect the semantic data layer and vector\/graph database integration guidelines. This allows LLM applications to securely map natural language queries directly to mature DaaS APIs, grounding the AI and preventing data hallucinations.<\/li>\n<li>Data architecture for autonomous agents: Design high-concurrency, immutable data snapshot patterns. This ensures that when multi-agent AI systems query network or commercial data simultaneously, they work from a consistent, synchronized state without causing database deadlocks or performance lags.<\/li>\n<li>AI data-sourcing and feature engineering standards: Establish standardized, reusable data-delivery interfaces for data scientists ensuring clean, governed telemetry is served with minimal latency.<\/li>\n<li>Next-gen visualization (\"Chat with Data\"): Explore, architect, and run proof of concepts (PoCs) for generative AI\/LLM integration (e.g., retrieval-augmented generation \/ RAG architecture), enabling business managers to ask natural language questions directly to the data lakehouse.<\/li>\n<\/ul>\n\n<p><strong>Architectural enablement for \"Intelligent Data Apps\"<\/strong><\/p>\n<ul>\n<li>Ensure the data infrastructure perfectly supports business-facing software products and future AI tools.<\/li>\n<li>Architecting for intelligent apps: Design the high-throughput, reusable data blueprints required to power complex internal software products (e.g., retail management system, roaming insights platforms). Ensure data flows seamlessly to support real-time calculations and predictive forecasting engines.<\/li>\n<li>Enterprise AI readiness assessment: Systematically audit the data estate to evaluate if the data is structurally ready for AI\/ML. Define architectural prerequisitesu2014such as feature stores and low-latency data pipelinesu2014needed to support production-grade AI models in these intelligent data apps.<\/li>\n<li>Next-gen visualization (\"Chat with Data\"): Enable this concept for internally developed intelligent data apps by designing a semantic layer.<\/li>\n<\/ul>\n\n<p><strong>Business alignment, governance, and lifecycle management<\/strong><\/p>\n<ul>\n<li>Translate business demand to tech strategy: Act as a high-level internal consultant to commercial, digital, and network business units. Translate complex commercial goals into structural data requirements to ensure technology investments directly unlock business value.<\/li>\n<li>Architecture review board (ARB) leadership: Act as a vital member of the data ARB, reviewing and approving technical designs submitted by various business units to prevent the creation of new data silos.<\/li>\n<li>Legacy decommissioning and technical debt management: Author the architectural \"sunsetting\" roadmaps for legacy telecom data silos to reduce corporate infrastructure costs and manage technical debt during major platform cutovers.<\/li>\n<li>Act as cross-functional orchestration and guardrails for data organization:<\/li>\n<li>Ensure the standard macro-ingestion and integration patterns (e.g., real-time event streaming standards vs. batch window architectures).<\/li>\n<li>Ensure data modeling is according to industry standard guidelines (aligning closely with TM Forum SID telecom models).<\/li>\n<li>Partner with governance to define architectural requirements for automated metadata cataloging, master data management (MDM) for entities like retail sales reps, and data lineage tracking.<\/li>\n<li>Ensure compliance mandates (GDPR, local telecom privacy laws) and zero-trust security architecture requirements into the macro designs, ensuring sensitive commissioning and network data is strictly protected.<\/li>\n<\/ul>\n\n<h4>Core competencies and qualifications<\/h4>\n<ul>\n<li><strong>Technical expertise:<\/strong> Strong understanding of modern data architectures (e.g., big data, data warehouse, AI systems, and real-time data streaming), tools, and programming languages.<\/li>\n<li><strong>Leadership:<\/strong> Ability to inspire and align diverse teams, manage complex projects, and influence cross-functional stakeholders.<\/li>\n<li><strong>Strategic thinking:<\/strong> Capable of balancing short-term deliverables with long-term vision and scalability.<\/li>\n<li><strong>Communication skills:<\/strong> Clear articulation of technical concepts to both technical and non-technical audiences.<\/li>\n<li><strong>Problem-solving:<\/strong> Proactive and solution-oriented, with the ability to tackle complex challenges under tight deadlines.<\/li>\n<li><strong>Agile community experience:<\/strong> Experience working in Agile teams to ensure delivery of needed quality gates and proactive actions.<\/li>\n<li><strong>Must have technical\/professional qualifications:<\/strong><\/li>\n<li>10+ years of experience in IT and maintaining large-scale data solutions.<\/li>\n<li>Knowledge of different vendors' technology in telecommunications and IT industry.<\/li>\n<li>Customer focus and ability to interact with decision makers.<\/li>\n<\/ul>\n\n<h4>Not a perfect fit?<\/h4>\n<p>Worried that you donu2019t 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 youu2019re excited about this role but your experience doesnu2019t 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>\n\n<h4>Who we are<\/h4>\n<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>\n<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 increasing diversity, ensuring equal representation, and making Vodafone a place everyone feels safe, valued, and included.<\/p>\n<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 application adjustments guidance provided by Vodafone.<\/p>\n\n<p><strong>Together we can.<\/strong><\/p><\/p><p><\/p>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>As Sr Data Engineer you will drive the design, deployment, and continuous optimization of scalable data pipelines that ingest and process a wide variety of structured and unstructured data sources into Mondia s AWS-based data warehouse and data lake. Implement and maintain reliable data ingestion, transformation, orchestration, monitoring, and CI/CD capabilities across the data platform. Promote operational excellence through automation, GitLab pipelines, Infrastructure as Code, observability, and robust engineering standards. Ensure that high-quality, secure, and well-governed data is available for reporting, advanced analytics, and AI- and machine-learning-enabled use cases across Mondia s business entities. Responsibilities: Collaborate with data engineers, data analysts, product and web analytics teams, software engineers, and business stakeholders in a collaborative and iterative environment. Provide technical guidance and contribute to the definition of data architecture, engineering standards, and reusable solutions across Mondia s data ecosystem. Design and maintain the data foundations required to deliver reliable internal data products, including well-defined datasets, data sources, dashboards, reports, and analytical solutions. Contribute as a senior member of the team to the reliable operation, performance, scalability, and cost efficiency of Mondia s AWS-based data platform, including Amazon Redshift, Athena, AWS Glue, Amazon S3, Step Functions, Lambda, EC2, and related AWS services. Design, build, test, deploy, monitor, and maintain end-to-end data pipelines and data management solutions using AWS Glue, Python, SQL, Spark/PySpark, and similar cloud-based ETL and data-processing technologies. Design and implement data models, schemas, tables, and storage structures across Amazon Redshift, Amazon S3, and the wider AWS data platform. Design and maintain orchestration patterns, workflows, event-driven components, and scheduling solutions using AWS Step Functions, AWS Glue Workflows, Amazon EventBridge, AWS Lambda, and similar technologies. Promote operational excellence through automation, GitLab CI/CD, Infrastructure as Code, observability, testing, documentation, and consistent engineering practices. Define, implement, and continuously improve automated data-quality and reliability controls, including checks for completeness, accuracy, consistency, validity, duplication, freshness, and reconciliation. Maintain appropriate data lineage, metadata, technical documentation, and ownership information to improve transparency, trust, and maintainability. Use appropriate programming languages, integration patterns, and engineering tools to connect systems and deliver reliable data solutions. Evaluate technologies based on the use case and adapt as platforms and requirements evolve. Use approved AI technologies and AI-assisted development tools as part of daily engineering activities to improve productivity, code quality, testing, documentation, troubleshooting, and solution design. Identify opportunities to integrate AI capabilities into data products where they provide measurable business or operational value. Communicate technical concepts, results, risks, and recommendations clearly to both technical and non-technical stakeholders across all levels of the organization. Document architectures, data flows, design decisions, operational procedures, and technical standards, while contributing constructively to technical discussions and engineering decisions. Comply with Mondia s policies, procedures, security requirements, and data-governance standards, while supporting the company s mission, vision, and values. Perform other reasonable job-related duties and responsibilities as assigned by the direct manager.</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p>Bachelor s degree in Computer Science/Engineering or Statistics. Skills &amp; Experience: +3 years of professional experience in Data Engineering or Data Warehousing with an integrative perspective, from management to operations involvement and hands-on experience with cloud architecture and cloud technologies such as AWS, Azure or Google Cloud Platform GCP. Strong proficiency in Python and SQL; experience with Scala, Java, or Bash/Shell scripting is an advantage. Solid experience with AWS data services, particularly Amazon Redshift, S3, Glue, Athena, Lambda, Step Functions, and EventBridge. Strong understanding of data warehouse, data lake, ETL/ELT, data modelling, and cloud data architecture concepts. Experience building and operating scalable data pipelines using AWS Glue, Spark/PySpark, or similar technologies. Good understanding of cloud security, identity and access management, data protection, monitoring, and logging. Experience with APIs, microservices, and event-driven integration patterns. Working knowledge of GitLab CI/CD, automation, Infrastructure as Code, and modern software engineering practices. Experience using AI-assisted development tools to improve engineering productivity and quality. Very good written and spoken English, with strong technical documentation and communication skills.</p><p></p></section>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> Introduction <br> <p>A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.</p><br><br> <br> <br> Your role and responsibilities <br> <p>As a Data Engineer specializing in Data Integration, you will design and build solutions to transfer data from operational and external environments to the business intelligence environment. You will utilize specialized tools to create and implement Extract, Transform, and Load (ETL) processes, ensuring the seamless flow of data throughout the business intelligence solution's lifecycle.</p><br><br><p>Your primary responsibilities will include:</p><br><br><p>* <strong>Design Data Integration Solutions:</strong> Create solutions to transfer data from operational and external environments to the business intelligence environment, utilizing tools such as Informatica, Ab Initio software, and DataStage.</p><br><br><p>* <strong>Implement ETL Processes:</strong> Develop and implement Extract, Transform, and Load (ETL) processes to ensure the seamless flow of data throughout the business intelligence solution's lifecycle.</p><br><br><p>* <strong>Utilize Specialized Tools:</strong> Apply knowledge of Informatica, Ab Initio software, and DataStage to design and build data integration solutions.</p><br><br><p>* <strong>Ensure Seamless Data Flow:</strong> Ensure the smooth flow of data throughout the business intelligence solution's lifecycle by creating and implementing effective ETL processes.</p><br><br><p>* <strong>Support Business Intelligence:</strong> Support the business intelligence environment by designing and building solutions to transfer data from operational and external environments.</p><br><br> <br> <br> Required education <br> Bachelor's Degree <br> <br> Required technical and professional expertise <br> <p>* <strong>Exposure to Data Integration Tools:</strong> Familiarity with tools such as Informatica, Ab Initio software, and DataStage (formerly Ascential) - IBM's WebSphere Data Integration Suite.</p><br><br><p>* <strong>ETL Process Implementation:</strong> Experience working with Extract, Transform, and Load (ETL) processes to ensure the seamless flow of data throughout the business intelligence solution's lifecycle.</p><br><br><p>* <strong>Data Solution Design:</strong> Exposure to designing solutions to transfer data from operational and external environments to the business intelligence environment.</p><br><br><p>* <strong>Business Intelligence Environment:</strong> Experience working within a business intelligence environment, supporting data integration solutions.</p><br><br><p>* <strong>Data Flow Management:</strong> Exposure to ensuring the smooth flow of data throughout the business intelligence solution's lifecycle.</p><br><br> <br> <br> Preferred technical and professional experience <br> <p>* <strong>Additional Data Integration Tools:</strong> Exposure to other data integration tools beyond Informatica, Ab Initio software, and DataStage can be beneficial in this role.</p><br><br><p>* <strong>Advanced ETL Techniques:</strong> Experience working with advanced ETL techniques and methodologies can enhance the ability to design and implement efficient data integration solutions.</p><br><br><p>* <strong>Business Intelligence Platforms:</strong> Familiarity with various business intelligence platforms can support the development of effective data integration solutions.</p><br><br> <br> <br> <br> <br> <br> </div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p><b>Key Responsibilities</b></p><ul><li><b>Build and maintain interactive</b> Power BI dashboards covering KPIs for all 5 subsidiaries</li><li>Design and manage Microsoft Access databases to store, organise, and query group-wide data</li><li>Develop complex DAX formulas, calculated measures, and Power Query transformations</li><li>Build sector-specific dashboards for operations, production, logistics, and sales</li><li>Analyse factory metrics including output volumes, quality rates, and waste</li><li>Prepare periodic and annual consolidated reports for group leadership</li><li>Ensure data accuracy and consistency across all sources and subsidiaries</li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>Bachelor s degree in Statistics, Data Science, Information Systems, or Engineering</li><li>3+ years of hands-on experience in data analytics roles</li><li>Advanced Power BI proficiency DAX, Power Query, data modeling, dashboard design</li><li>Hands-on Microsoft Access experience database design, queries, relationships, automated reports</li><li>Advanced Excel complex formulas, pivot tables, dynamic arrays</li><li>SQL is a strong advantage for data extraction and cross-system integration</li><li>Manufacturing or logistics data experience is an advantage</li><li>Strong attention to data accuracy, consistency, and timely delivery</li></ul><p></p></section>