Data Engineer.Egypt-MIS-HO.International Banking Group

To design and maintain batch data pipelines, drive data strategy, and enhance data architecture & best practices. This role requires deep expertise in core banking, retail, digital, marketing, risk, and compliance systems across multiple regions (UAE, Egypt, Pakistan, etc.). The function spans Enterprise Data Lake, Azure Data Lake, BI, Advanced Analytics, and Real-time Streaming platforms. Responsibilities include developing on-prem & cloud data solutions, managing change releases & resources, and delivering critical data insights for strategic decision-making, regulatory compliance, and operational efficiency.

• Data Engineering & Architecture: Design, develop, and maintain scalable real-time & batch data pipelines to support increasing data demands.
• Data Domains & Governance: Establish data domains across banking products and lay the foundation for Data Mesh architecture while ensuring data security, governance, and compliance.
• Data Platform Management: Oversee ETL processes, data modelling, integration, orchestration, and automation for seamless data operations.
• Collaboration & Business Alignment: Work with analysts, data scientists, and business teams to improve data models, enhance accessibility, and enable data-driven decision-making.
• Production Support & Monitoring: Provide L2/L3 support, debug data issues, and ensure high availability & quality of production data.
• Risk & Compliance: Implement risk controls, audit reviews, RCSA, and maintain compliance with data privacy regulations through access controls, encryption, and masking.
• Performance Optimization & Scalability: Identify and mitigate bottlenecks, forecast storage & processing needs, and ensure a scalable data infrastructure.
• Incident & Change Management: Coordinate with incident teams, change management boards, and vendors to ensure timely resolutions, approvals, and production deployments.
• Innovation & Best Practices: Stay updated on industry trends, implement emerging technologies, and continuously improve data engineering processes.

Knowledge:

• Data engineer with a solid technical background and experience in data-intensive systems (> 15 years)
• Demonstrate deep knowledge and experience in databases, Datamart's, Data Modelling, Data Governance, Data Security, BI tools, ETL Solutions.
• Experience in Automating Deployment, scheduling, monitoring, and management of self-serve authorized data sets.
• Proficiency in relational SQL, Graph and NoSQL databases.
• Proficiency in Elastic Search and Couchbase databases 
• In-depth skills in developing and maintaining ETL/ELT data pipelines. 
• Understand business problems and provide data-driven solutions for those problems.
• Requirement Gathering – collaborate with business and technology teams to understand requirements and share with the technical team. 
• Gap Analysis - Understand and analyze business process flows and impact on technology flows. Translated regulatory/functional requirements into functional technical requirement documents. 
• Strong communication skills (verbal/written) to deliver technical insights and interpret data reports to the clients. An analytical mind and inclination for problem-solving

Core Skills:

• Big Data Engineering (Data Lake- Cloudera Azure DL), Data Bricks & SQL Concepts
• Data Architect, Modelling, Governance
• Domain Knowledge in Banking/Finance area
• Data Analytics & Data Management Fundamentals
• DevOps & Agile Methodology
• Data Streaming solutions, API Integration, Cloud Powered Platform 
• Team Management, Leadership & Communication Skills

Experience:

• Strong experience in Big Data, Hadoop Ecosystem, Spark Streaming, Kafka, Python, SQL, Hive, NIFI, Airflow
• Proficient with Azure Cloud services such as Azure Data Factory (ADF), Databricks, ADLS, Azure Synapse, Logic Apps, Azure Functions. Or similar data stack knowledge within Google/AWS cloud services
• Proficiency in relational SQL, Graph and NoSQL databases.
• Proficiency in Elastic Search and Couchbase databases 
• In-depth skills in developing and maintaining ETL/ELT data pipelines. 
• Experience in data modelling techniques such as Kimball star schema, 3NF, vault modelling etc.
• Experience in workflow management tools such as Airflow, Oozie and CI/CD tools
• Data streaming solution in Kafka or Confluent Kafka 
• Hands on experience in Google Big Query, Google Analytics & Clickstream Data Model
• Reporting knowledge in Power BI, Tableau, Qlik etc.