Data Entry Jobs in Egypt

JOB PURPOSEResponsible for creating, maintaining, validating, and governing master data across the organization to ensure data accuracy, consistency, and integrity. The role supports business operations by managing master data related to materials, customers, vendors, products, pricing, and organizational structures while ensuring compliance with data governance standards and ERP requirements.<br>RESPONSIBILITIES<br>Data Management Maintains accurate, complete, and consistent master data across ERP systems to support business operations and decision-making. Data Governance Ensures compliance with master data standards, governance policies, and data quality requirements. Business Support Works closely with cross-functional teams to support business processes through timely creation and maintenance of master data. Work Scheduling / Allocation Prioritizes and manages daily master data requests while ensuring agreed service levels are achieved.<br>TASKS• Create, maintain, update, and validate master data within the ERP system.• Manage Material Master, Item Master, Customer Master, Vendor Master, Product Master, Pricing Master, and Bills of Materials (BOMs).• Review and verify all master data creation and modification requests before implementation.• Ensure master data accuracy, completeness, consistency, and integrity across all systems.• Monitor and eliminate duplicate or inaccurate master data records.• Maintain data classification, coding structures, and naming conventions according to company standards.• Coordinate with Supply Chain, Procurement, Production, Planning, Sales, Finance, and IT to ensure accurate master data requirements.• Support new product launches by creating all required master data records and system configurations.• Perform periodic data cleansing, validation, and reconciliation activities.• Generate reports related to master data quality, completeness, and accuracy.• Support ERP implementation, upgrades, testing, and system enhancements related to master data.• Investigate and resolve master data issues affecting business operations.• Ensure compliance with internal controls, company policies, and data governance procedures.• Participate in process improvement initiatives to enhance master data quality and operational efficiency.• Maintain proper documentation for all master data requests and approvals.<br>EXPERIENCE1-3 years equivalent work experience.<br>EDUCATIONBachelor’s degree in business administration, Information System or Computer Science

A leading AI and Data Consultancy in the Gulf region is expanding its operations and seeking highly qualified Arabic-speaking professionals to join its team in the Kingdom of Saudi Arabia (KSA) and Qatar. This is a unique opportunity to be part of a forward-thinking organization driving data transformation and AI-based governance solutions across the region.???? Open Positions1. Senior Consultant – Data Management & Governance Experience: Minimum 10+ years in data management and governance Key Responsibilities:Lead the design, development, and implementation of enterprise-level data governance frameworks. Establish and oversee data standards, policies, and compliance in alignment with international and national frameworks (e.g., DAMA, National Planning Council). Collaborate with internal and government stakeholders to ensure effective data lifecycle management and regulatory alignment. Drive data maturity assessments and recommend strategic improvements. Support AI-driven data initiatives and ensure their governance alignment. Requirements:Proven track record in data strategy, metadata management, data quality, and master data management. Deep knowledge of data governance frameworks (e.g., DAMA-DMBOK). Excellent communication and stakeholder management skills. Fluency in Arabic is mandatory.2. Data Management Specialists Experience: 4–6 years in data management, governance, or related domains Key Responsibilities:Support the development and implementation of data management and governance frameworks. Manage and monitor data quality, metadata, and compliance activities. Contribute to policy creation, documentation, and governance reporting. Collaborate with business units and IT teams to ensure proper data stewardship practices. Requirements:Experience in data quality management, data lineage, and metadata documentation. Knowledge of national data programs and standards. Strong analytical and problem-solving skills. Arabic proficiency is required.???? Preferred Professional Certifications Candidates with the following certifications will be given preference:Certified Data Management Professional (CDMP) Certified Data Governance Professional (CDGP – DAMA) Data Governance & Stewardship Professional (DGSP) The Open Group Architecture Framework (TOGAF)???? Core Competencies & Expertise In-depth understanding of local data governance regulations and frameworks issued by national authorities (e.g., National Planning Council). Familiarity with the National Data Program and collaboration with government entities. Strong grasp of DAMA-DMBOK principles and data architecture practices. Experience in AI-driven data strategy, digital transformation, and advanced analytics governance is a strong advantage. Excellent leadership, coordination, and cross-functional collaboration skills.???? Role Details???? Location: Kingdom of Saudi Arabia (KSA) or Qatar???? Industry: AI & Data Consultancy???? Employment Type: Full-time, On-site???? Languages: Arabic (mandatory), English (professional proficiency)

A leading AI and Data Consultancy in the Gulf region is expanding its operations and seeking highly qualified Arabic-speaking professionals to join its team in the Kingdom of Saudi Arabia (KSA) and Qatar. This is a unique opportunity to be part of a forward-thinking organization driving data transformation and AI-based governance solutions across the region.???? Open Positions1. Senior Consultant – Data Management & Governance Experience: Minimum 10+ years in data management and governance Key Responsibilities:Lead the design, development, and implementation of enterprise-level data governance frameworks. Establish and oversee data standards, policies, and compliance in alignment with international and national frameworks (e.g., DAMA, National Planning Council). Collaborate with internal and government stakeholders to ensure effective data lifecycle management and regulatory alignment. Drive data maturity assessments and recommend strategic improvements. Support AI-driven data initiatives and ensure their governance alignment. Requirements:Proven track record in data strategy, metadata management, data quality, and master data management. Deep knowledge of data governance frameworks (e.g., DAMA-DMBOK). Excellent communication and stakeholder management skills. Fluency in Arabic is mandatory.2. Data Management Specialists (x2) Experience: 4–6 years in data management, governance, or related domains Key Responsibilities:Support the development and implementation of data management and governance frameworks. Manage and monitor data quality, metadata, and compliance activities. Contribute to policy creation, documentation, and governance reporting. Collaborate with business units and IT teams to ensure proper data stewardship practices. Requirements:Experience in data quality management, data lineage, and metadata documentation. Knowledge of national data programs and standards. Strong analytical and problem-solving skills. Arabic proficiency is required.???? Preferred Professional Certifications Candidates with the following certifications will be given preference:Certified Data Management Professional (CDMP) Certified Data Governance Professional (CDGP – DAMA) Data Governance & Stewardship Professional (DGSP) The Open Group Architecture Framework (TOGAF)???? Core Competencies & Expertise In-depth understanding of local data governance regulations and frameworks issued by national authorities (e.g., National Planning Council). Familiarity with the National Data Program and collaboration with government entities. Strong grasp of DAMA-DMBOK principles and data architecture practices. Experience in AI-driven data strategy, digital transformation, and advanced analytics governance is a strong advantage. Excellent leadership, coordination, and cross-functional collaboration skills.???? Role Details???? Location: Kingdom of Saudi Arabia (KSA) or Qatar ???? Industry: AI & Data Consultancy ???? Employment Type: Full-time, On-site ???? Languages: Arabic (mandatory), English (professional proficiency)

Nawy Proptech is in search of a highly motivated and talented Data Engineer to become a valuable addition to our dynamic team. As a Data Engineer at Nawy, you will play a key role in data management, ensuring data quality, integrity, and modeling. We are seeking an individual with a strong technical background, hands-on experience with data processing technologies, and a passion for building robust and efficient data solutions.<br><br>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 APIsOptimize 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<br><br>Requirements<br><br>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 1 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

Müller's Solutions is on the lookout for a talented Data Architect to join our team. In this role, you will be responsible for designing and implementing comprehensive data architectures that align with the organization's strategic goals. Your expertise will contribute to managing data effectively, ensuring high data quality, and supporting data analytics efforts across various departments. You will collaborate with cross-functional teams to drive the development of innovative data solutions that enhance business processes.<br><br>Responsibilities:<br><br>Design, implement, and manage complex data architectures that support business objectives Develop and maintain data models, database schemas, and data flow diagrams Collaborate with business analysts and stakeholders to gather data requirements and translate them into architectural specifications Establish and enforce data governance policies and best practices Conduct data quality assessments and implement solutions for data cleansing and accuracy Oversee data integration efforts with various systems, ensuring seamless data flow Work with IT teams to optimize database performance and storage solutions Continuously evaluate and adopt new technologies to enhance data architecture Provide mentorship and guidance to junior data professionals Stay updated on industry trends and advancements in data architecture and management<br><br>Requirements<br><br>Requirements:<br><br>Bachelor's degree in Computer Science, Information Technology, or related field Proven experience as a Data Architect or a similar role Strong expertise in data modeling and database design Experience with data integration tools and ETL processes Familiarity with data governance frameworks and best practices Proficient in SQL, as well as experience with database management systems (e.g., Oracle, SQL Server, MySQL) Solid understanding of data security principles and practices Analytical mindset with excellent problem-solving skills Strong communication and interpersonal skills Ability to work collaboratively in a team-oriented environment<br><br>Benefits<br><br>Why Join Us:<br><br>Opportunity to work with a talented and passionate team.<br><br>Competitive salary and benefits package.<br><br>Exciting projects and innovative work environment.

Company Description Q-market is a growing organization focused on leveraging data to optimize market performance and operational efficiency. Based in Cairo, Egypt, the company aims to transform complex information into clear insights that support strategic decision-making. Q-market values innovation, accuracy, and collaboration, and encourages employees to contribute ideas that improve data processes and business outcomes. Team members work in a dynamic environment where data-driven thinking is central to product development and organizational strategy. Role Description The Director, Data Cycle will oversee the end-to-end lifecycle of data within Q-market, ensuring data is collected, stored, processed, and utilized efficiently and securely. This full-time, on-site role in Cairo, Egypt includes leading the data strategy, defining governance frameworks, and coordinating with cross-functional teams to align data practices with business goals. Day-to-day responsibilities include managing data acquisition and integration, monitoring data quality, optimizing data pipelines and workflows, and identifying opportunities to improve analytics and reporting. The Director will also supervise data teams, establish standards and best practices, and partner with leadership to support strategic initiatives through robust data insights. The role requires a hands-on approach to solving complex data challenges while mentoring team members and promoting a culture of data excellence. Qualifications Strong experience in data lifecycle management, including data collection, storage, integration, and archiving. Proficiency in data governance, data quality frameworks, and compliance with relevant data regulations and standards. Hands-on expertise with databases, data warehousing, ETL/ELT tools, and modern data pipeline architectures. Demonstrated ability to use analytics and business intelligence tools to generate actionable insights and performance metrics. Proven leadership experience managing data or analytics teams, with the ability to set strategy and drive execution. Excellent problem-solving, organizational, and stakeholder communication skills, including the ability to explain complex data topics clearly. Bachelor’s or Master’s degree in Data Science, Computer Science, Information Systems, Engineering, or a related field. Experience working in market intelligence, retail, or a similar data-rich environment is an advantage. Ability to work on-site in Cairo, Egypt and collaborate effectively with cross-functional teams.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>We are looking for a motivated and technically solid L1 Data Engineer to join our growing Data &amp; Analytics team. In this role, you will be responsible for designing, building, and maintaining the data architecture and infrastructure that supports our organization's data strategy. You will work hands-on to develop, test, and deploy reliable data solutions — ensuring pipelines are scalable, efficient, and aligned with business requirements.</p><br><p>This is an ideal opportunity for a data professional who is eager to deepen their expertise in cloud-native data platforms, particularly within the Microsoft Azure and Databricks ecosystem, and who thrives in a collaborative, fast-paced environment.</p><br><p><strong>KEY RESPONSIBILITIES</strong></p><br><p>• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows to support business intelligence and analytics use cases.</p><br><p>• Build and optimize data ingestion processes using Azure Data Factory and Databricks, ensuring data quality and consistency across all layers of the data platform.</p><br><p>• Transform and process large datasets using PySpark and Python, applying best practices for performance and maintainability.</p><br><p>• Write and optimize complex SQL queries to support analytical reporting and data validation requirements.</p><br><p>• Collaborate with data architects and senior engineers to implement and maintain data models aligned with organizational standards.</p><br><p>• Monitor, troubleshoot, and resolve pipeline failures and data quality issues, applying root-cause analysis to prevent recurrence.</p><br><p>• Contribute to documentation of data pipelines, data dictionaries, and engineering standards.</p><br><p>• Support the team in exploring and evaluating new tools and approaches to continuously improve the data infrastructure.</p><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Description</span><br><span></span><p><b><span>JOB PURPOSE</span></b></p><br><p><span>To develop an end-to-end analytical data governance control to maintain a high level quality for the organization’s data assets and ensure its fitness to use across systems. Working with business stakeholders to set data standards, develop data quality analytical assessments and monitoring reports/dashboards to highlight the data defects. In addition to preparing and executing data remediation exercises.</span></p><br><p><b><span>KEY ACCOUNTABILITIES</span></b></p><br><p><b><span>Roles and Responsibilities</span></b></p><br><p><span><span>1.</span></span><span>Perform the required data exploration activities needed to set proper data elements standards using </span><span>machine learning, data mining, and data quality techniques.</span></p><br><p><span><span>2.</span></span><span>Identifying data quality defects patterns and trends and perform root-cause analysis, gap analysis, and impact analysis in order to solve complex data issues.</span></p><br><p><span><span>3.</span></span><span>Develop Data Quality analytical reports in order to provide operational and tactical data stewards with monitoring and tracking tools to eliminate Data Quality defects.</span></p><br><p><span><span>4.</span></span><span>Develop Data Quality Dashboards to provide senior management and business managers with proper visual monitoring tools in order to monitor and track the progress of eliminating data defects.</span></p><br><p><span><span>5.</span></span><span>Collaborate with other business areas that are sourcing and consuming data to align expectations as part of developing requirements, creating and executing test plans and to effectively support production processing.</span></p><br><p><span><span>6.</span></span><span>Develop data remediation plans for the data failures in order to meet the required standard to enhance data quality level, and measure progress after execution to ensure the successful execution of the remediation process.</span></p><br><p><span><span>7.</span></span><span>Apply the data governance framework including the management of data, operating model, data policies and standards in order to deliver a smooth operation process.</span></p><br><p><span><span>8.</span></span><span>Assess the changes on Reference Data to ensure they match the predefined quality standards and ensure they meet the business and regulatory rules.</span></p><br><p><span><span>9.</span></span><span>Participate in the required </span><span>research and </span><span>POCs to explore and implement new technology trends and complex data governance use cases in order to enhance the enterprise data governance operating model.</span></p><br><p><span><span><span>10.</span></span></span><span>Apply the data management framework including the management of data, information and analytics operating model, data policies and standards in order to deliver a smooth operation process</span><span><span>.</span></span></p><br><p><b><span>Policies, Processes and Procedures</span></b></p><br><p><span><span>11.</span></span><span>Follow all relevant department policies, processes, standard operating procedures and instructions so that work is carried out in a controlled and consistent manner </span></p><br><p><b><span>Day-to-day Operations</span></b></p><br><p><span><span>12.</span></span><span>Follow the day-to-day operations related to own jobs in the department to ensure continuity of work </span></p><br><p><b><span>Compliance</span></b></p><br><p><span><span>13.</span></span><span>Comply with all relevant CBE regulations, banking laws, AML regulations and internal CIB policies and code of conduct in order to maintain CIB’s sound legal position and mitigate any potential risks</span></p><br><p><span><span>14.</span></span><span>Monitor and ensure that Data-related decisions, processes, and controls subject to Data are auditable; </span></p><br><p><span><span>§</span></span><span>Metadata should be timely updated to reflect the real situation.</span></p><br><p><span><span>§</span></span><span>Data architecture should be always up-to-date and reflecting the existing facts. </span></p><br><p><span><span>§</span></span><span>Documentation should be available to support compliance-based and operational auditing requirements.</span></p><br><br> <br> <span>Qualifications</span><br><span></span><p><b><span>QUALIFICATIONS, EXPERIENCE, &amp; SKILLS</span></b></p><br><p><b><span>Qualifications &amp; Experience</span></b></p><br><p><span><span>§</span></span><span>Bachelor’s degree of Information Systems, Computer Science or its equivalent</span></p><br><p><span><span>§</span></span><span>Analyst: 2 - 4 years of previous work experience </span></p><br><p><span><span>§</span></span><span>Experience in data analysis, data governance, information governance, data management, or data analytics related jobs would be a plus.</span></p><br><p><span><span>§</span></span><span>Good Knowledge in database concept and PL-SQL, BI concepts (ETLs, Cubes, Dashboards, Reports...etc.) is a must</span></p><br><p><span><span>§</span></span><span>Good Knowledge in Python or R is a must</span></p><br><p><span><span>§</span></span><span>Good Knowledge in Data Mining techniques and dealing with huge data sets is a plus</span></p><br><p><span><span>§</span></span><span>Good Knowledge in Data Visualization tools is a plus</span></p><br><p><b><span>Skills</span></b></p><br><p><span><span>§</span></span><span>Strong Analytical skills with a high degree of accuracy</span></p><br><p><span><span>§</span></span><span>Strong Problem Solving and Data Manipulation Skills</span></p><br><p><span><span>§</span></span><span>Ability to analyze Complex business problems</span></p><br><p><span><span>§</span></span><span>Ability to exercise good judgment and discretion, especially with regards to sensitive or confidential personnel and organizational matters</span></p><br><p><span><span>§</span></span><span>Demonstrated ability to 1) effectively work in an ambiguous environment, 2) effectively work in a cross-team environment and 3) succeed in a complex and dynamic work environment.4) Work independently, directly with the business partners.</span></p><br><p><span><span>§</span></span><span>Strong interpersonal and communication skills; ability to develop and maintain effective working relationships with persons at all levels in the organization</span></p><br><p><span><span>§</span></span><span>High energy and high endurance; ability to respond flexibly and positively in all circumstances; calm under pressure and tight deadlines</span></p><br><p><span><span>§</span></span><span>Strong organizational skills; ability to work independently and to prioritize a heavy workload of competing assignments</span><br></p><br><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>We are looking for a highly skilled and experienced L2 Data Engineer to join our growing Data &amp; Analytics team. In this role, you will lead the design, development, optimization, and maintenance of scalable enterprise data platforms and cloud-native data solutions. You will work closely with architects, analysts, and business stakeholders to build high-performance data pipelines and modern lakehouse solutions that support advanced analytics, reporting, and data-driven decision-making.</p><br><p>This opportunity is ideal for a senior data professional with strong hands-on expertise in Databricks and the Microsoft Azure ecosystem, who is passionate about building reliable, scalable, and optimized data platforms in enterprise environments.</p><br><p><strong>KEY RESPONSIBILITIES</strong></p><br><p>• Design, develop, and optimize enterprise-scale data pipelines and ETL/ELT workflows using Azure and Databricks technologies.</p><br><p>• Architect and implement scalable data ingestion, transformation, and orchestration processes using Azure Data Factory, Databricks, and Azure Synapse Analytics.</p><br><p>• Develop high-performance data transformation frameworks using PySpark, Python, and Spark SQL for large-scale distributed data processing.</p><br><p>• Optimize SQL queries, Spark jobs, and data workflows to improve performance, scalability, and cost efficiency.</p><br><p>• Lead data migration initiatives, including SQL Server migrations and modernization of legacy data platforms.</p><br><p>• Implement and maintain Delta Lake architecture, incremental data loading strategies, and enterprise data lake best practices.</p><br><p>• Collaborate with architects and cross-functional teams to design robust and scalable data models aligned with business and governance standards.</p><br><p>• Monitor and troubleshoot production pipelines, perform root-cause analysis, and implement preventive measures for recurring issues.</p><br><p>• Support CI/CD implementation and infrastructure automation for data engineering workflows.</p><br><p>• Mentor junior engineers and contribute to engineering standards, reusable frameworks, and technical best practices.</p><br><p>• Create and maintain technical documentation including architecture diagrams, pipeline documentation, and operational runbooks.</p><br><p>• Evaluate and recommend modern data engineering tools, frameworks, and optimization strategies.</p><br> </div>

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>As a Data Engineer He/She will be responsible for designing, building, and maintaining the data architecture and infrastructure required for our organization's data needs. will also be responsible for developing, testing, and deploying data solutions, ensuring that they meet our organization's needs.</p> <ul> <li><strong>+2 years of experience</strong> in Data Engineering</li> <li>Strong knowledge of Python for data processing and analysis</li> <li>Hands-on experience with Pandas and PySpark</li> <li>Experience with Databricks and Azure Data Factory</li> <li>Basic experience with Azure Synapse Spark</li> <li>Good SQL querying and optimization skills</li> <li>Experience in data pipelines and ETL workflows</li> <li>Knowledge aligned with Databricks Certified Data Engineering Associate</li> <li>Nice to have: SQL Server migration and Terraform for Azure</li> <li>L1 knowledge assessed in the Databricks certification: Databricks Certified Data Engineering Associate</li> </ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p>+2 years of experience in Data Engineering Strong knowledge of Python for data processing and analysis Hands-on experience with Pandas and PySpark Experience with Databricks and Azure Data Factory Basic experience with Azure Synapse Spark Good SQL querying and optimization skills Experience in data pipelines and ETL workflows Knowledge aligned with Databricks Certified Data Engineering Associate Nice to have: SQL Server migration and Terraform for Azure L1 knowledge assessed in the Databricks certification: Databricks Certified Data Engineering Associate</p><p></p></section>

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 APIsOptimize 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<br><br>Requirements<br><br>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

Skillset: Enterprise Data Architecture, Azure data bricks. Integrations · Multi-Layer Platform. Data layer design We are building enterprise-grade data tools that sit on top of complex, existing customer environments and build a reusable data platform powering multiple products and client deployments. We need someone who has built data platforms before, not just pipelines, and can design a data layer that blends seamlessly into whatever stack our customer already runs.<br>Job Description Design and own the data architecture layer that sits across all our enterprise products Map and integrate into customer environments cloud warehouses, on-prem databases, legacy systems, third-party APIsBuild reusable data connectors, transformation pipelines, and a normalization layer that works regardless of the source Define the canonical data models our products are built on — consistent, versioned, and documented Work with product and AI teams to ensure data is structured correctly for downstream agent and analytics use cases Own data quality — schema validation, lineage tracking, and monitoring across all pipelines Guide technical decisions on storage, processing, and integration tooling as the platform scales<br>Responsibilities <br>Data Architecture & Modeling Designing multi-layer data architectures (raw → curated → serving) Canonical schema design, data contracts, and versioned data models Data vault, dimensional modeling, or Lakehouse patterns depending on context<br>Integration & Connectivity & Orchestration Deep experience connecting to heterogeneous enterprise environments REST APIs, Graph QL, webhooks, EDI, SFTP, and enterprise middleware (Mule Soft, Boomi, or similar) Database connectors across SQL (Postgres, SQL Server, Oracle) and NoSQL (Mongo DB, Dynamo DB, Cosmos DB) . Airflow, Prefect, or Dagster for pipeline orchestration PySpark or SQL-based batch processing at scale<br>Data Platforms & Storage Cloud data warehouses: Snowflake, Big Query, Redshift, Azure Synapse Data lake/Lakehouse: Databricks, Delta Lake, Apache Iceberg Streaming: Kafka, Kinesis, or Pub/Sub for real-time data flows Vector databases (pgvector, Pinecone, Weaviate) for AI-adjacent use cases<br>Software Engineering Fundamentals Python (strong) — data engineering, scripting, SDK/library development Infrastructure as code: Terraform, Pulumi, or Cloud Formation CI/CD for data pipelines — testing, versioning, deployment automation API design and SDK delivery so downstream teams consume data cleanly <br>Enterprise & Customer Context Experience deploying into customer-managed environments (not just Saa S) Understanding of enterprise data governance, compliance, and access control requirements Ability to read an existing customer architecture and design around it — not replace it

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>Design and deliver end-to-end <strong>conceptual, logical, and physical data models</strong> across enterprise environments, with a strong focus on data warehousing</p> <ul> <li>Lead and contribute to <strong>data mapping (SMX)</strong>, integration design, and model alignment with ETL and BI layers</li> <li>Work directly with clients across <strong>banking, telecommunications, and government sectors</strong> to translate business requirements into scalable data solutions</li> <li>Adapt to dynamic project environments, supporting multiple initiatives and evolving data landscapes</li> <li>Ensure modeling best practices, data consistency, and scalability across implementations</li> </ul> <p>A dynamic Data Modeling consulting team supporting multiple enterprise projects across Egypt</p> <ul> <li>Cross-functional teams including ETL developers, BI engineers, architects, and client stakeholders</li> <li>The role reports to the <strong>Data Modeling Consulting Manager</strong></li> <li>You will play a key role in bridging business and technical teams, ensuring high-quality data design and delivery</li> </ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p>5 7 years of experience in data modeling, with at least 2 years of full-lifecycle modeling experience</p> <ul> <li>Advanced expertise in conceptual, logical, and physical data modeling</li> <li>Proficiency in data modeling tools such as Erwin or PowerDesigner</li> <li>Hands-on experience in data mapping and data migration projects</li> <li>Strong communication and stakeholder management skills</li> </ul><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 various tools to create and implement Extract, Transform, and Load (ETL) processes, ensuring the seamless flow of data throughout the business intelligence solution's lifecycle. Your primary responsibilities will include: * Design Data Integration Solutions: 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. * Implement ETL Processes: Develop and implement Extract, Transform, and Load (ETL) processes to ensure the seamless flow of data throughout the business intelligence solution's lifecycle. * Utilize Data Integration Tools: Apply knowledge of Informatica, Ab Initio software, and DataStage to design and build data integration solutions. * Ensure Seamless Data Flow: Ensure the smooth flow of data throughout the business intelligence solution's lifecycle by creating and implementing efficient ETL processes. * Support Business Intelligence: 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>* Exposure to Data Integration Tools: Familiarity with tools such as Informatica, Ab Initio software, and DataStage, with the ability to apply this knowledge to design and build data integration solutions. * Experience with ETL Processes: Understanding of Extract, Transform, and Load (ETL) processes, with the ability to develop and implement these processes to ensure seamless data flow. * Data Solution Design: Exposure to designing solutions to transfer data from operational and external environments to the business intelligence environment. * Data Flow Management: Experience working with data flows, with the ability to ensure the smooth flow of data throughout the business intelligence solution's lifecycle. * Business Intelligence Support: Exposure to supporting business intelligence environments, with the ability to design and build solutions to transfer data from operational and external environments.</p><br><br> <br> <br> Preferred technical and professional experience <br> <p>* Additional Data Integration Tools: Exposure to other data integration tools beyond Informatica, Ab Initio software, and DataStage, with the ability to quickly learn and apply new tools to design and build data integration solutions. * Advanced ETL Process Development: Experience with complex ETL process development, including data mapping, data transformation, and data quality checks, to ensure seamless data flow throughout the business intelligence solution's lifecycle. * Business Intelligence Environment Knowledge: Exposure to various business intelligence environments, with the ability to design and build solutions to transfer data from operational and external environments to support business intelligence initiatives.</p><br><br> <br> <br> <br> <br> <br> </div>

Job Responsibilities:Lead the design and implementation of data pipelines and governance frameworks using IBM CP4D, ensuring enterprise data is reliable, governed, and accessible. Design and develop enterprise data pipelines using IBM Data Stage on CP4DImplement data governance and cataloging practices using Watson Knowledge Catalog Integrate CP4D with external data sources and services Define best practices for IBM-based data architecture Collaborate with BI and analytics teams to support reporting needs Mentor and support junior engineers working within CP4DParticipate in strategic planning and technical roadmap development<br><br>Required Qualifications:Bachelor’s degree in Communications Engineering, Computer Science, or a related field.5+ years in data engineering, including 3+ years with IBM Cloud Pak for Data (CP4D) Expert in IBM Data Stage, Watson Knowledge Catalog, and Data Virtualization Strong understanding of ETL/ELT pipelines, data governance, and metadata management Proficient in SQL, Python, and REST APIsStrong troubleshooting and performance optimization skills Ability to mentor junior team members and lead implementation projects.

About the Role We are looking for an experienced Project Manager – Data, Analytics & AI to lead and coordinate projects across our data and analytics initiatives. In this role, you will work closely with data engineers, data analysts, and AI/ML teams to ensure the successful delivery of data-driven solutions that support business decision-making and innovation across our digital banking platform. The ideal candidate has strong experience managing data and analytics projects, coordinating cross-functional technical teams, and delivering complex technology initiatives. Key Responsibilities Project Management Lead end-to-end delivery of data, analytics, and AI-related projects. Define project scope, timelines, milestones, and deliverables. Ensure projects are delivered on time, within scope, and within budget. Collaboration Work closely with data engineers, data scientists, analysts, and product teams. Facilitate communication between technical teams and business stakeholders. Data & Analytics Initiatives Manage initiatives related to data platforms, analytics solutions, and AI models. Coordinate implementation of data pipelines, reporting tools, and analytics platforms. Monitoring & Reporting Track project progress and ensure alignment with business objectives. Identify risks, dependencies, and potential bottlenecks. Process Optimization Improve project delivery processes and data team collaboration. Ensure alignment with Agile or hybrid delivery frameworks. Required Qualifications Experience Minimum 3+ years of experience in project management Proven experience managing data, analytics, or technology projects Project management certifications such as PMP, PRINCE2, or Agile certifications Technical Understanding Strong understanding of data platforms, analytics tools, or AI/ML workflows Experience working with data engineering or analytics teams Methodologies Experience with Agile, Scrum, or hybrid project management frameworks Professional Skills Strong stakeholder management skills Excellent communication and leadership abilities Strong analytical and problem-solving skills Preferred Qualifications Experience in data analytics, AI, or machine learning projects Experience working in financial services, fintech, or digital banking Familiarity with data platforms, data warehouses, or BI tools

About the Role We are looking for a Technical Data Analyst to join our Data Management and AI team and contribute to building data-driven solutions that power our digital banking platform. In this role, you will work closely with engineering, analytics, and business teams to gather requirements, design data processes, and support data integration initiatives. You will play a key role in enabling accurate data analysis and reporting to support business decisions and enhance the customer banking experience. This is an excellent opportunity for a junior data professional looking to grow within a fast-paced fintech environment. Team Overview The Data Management and AI team works across the full technology stack within QNBeyond Plus, enabling advanced analytics, data management, and AI-driven capabilities. Our team collaborates with multiple technology and product teams to manage, analyze, and serve data that drives innovative digital banking experiences for our customers. Key Responsibilities Data Analysis & Collaboration Act as a bridge between technical teams and data stakeholders. Gather and document reporting and data requirements. Collaborate with engineering and analytics teams to support data initiatives. Data Engineering Support Translate integration requirements into procedures, scripts, and technical documentation. Assist in designing data ingestion pipelines. Data Quality & Verification Design and support data validation and verification procedures. Ensure data accuracy, integrity, and reliability across systems. Project Delivery Support data initiatives and drive assigned tasks to completion. Contribute to Agile processes and cross-team collaboration. What We Are Looking For You must be:Self-motivated, driven to take initiative and achieve results A team player, eager to collaborate and learn A problem solver, focused on identifying solutions Customer-oriented, committed to delivering high-quality results Detail-oriented, especially regarding security and compliance Adaptable to a growing fintech environment Qualifications Technical Skills Strong knowledge of SQLUnderstanding of data modeling concepts Knowledge of programming or scripting tools Professional Skills Strong verbal and written communication skills Experience with requirements gathering and documentation Domain Knowledge Understanding of banking or financial services is a plus Experience in regulated environments or PCI/DSS compliance is advantageous Experience2+ years of experience in software engineering, data analysis, or system analysis At least 1 year of experience in fintech or regulated environments is preferred