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Location: UAE, on-site
Engagement model: Full-time
Role Summary
Timely, reliable data pipelines are what turn a platform design into business value. The Data Engineer builds and operates pipelines that move data from source systems into the lakehouse and on to analytics and AI consumers. They ensure that the pipelines are automated, performant, secure, and governed.
The role works alongside the data architect, data quality engineer, business analysts, and AI engineers. Its job is to deliver production-grade pipelines on Azure / Microsoft Fabric, with metadata and lineage captured in Microsoft Purview.
Key Responsibilities on the Client's Engagement
- Pipeline development: Build batch, incremental, CDC, and streaming ingestion pipelines from source systems into the Bronze layer, using Azure Data Factory and Fabric pipelines.
- Transformation: Develop Silver- and Gold-layer transformations in SQL, PySpark, and Spark notebooks, including cleansing, conformance, enrichment, and business-rule logic.
- Data modelling implementation: Implement dimensional models, SCDs, surrogate keys, and data marts according to the architect's designs.
- Embedded quality controls: Integrate DQ checks, validation, quarantine, and reconciliation into pipelines in partnership with the Senior Data Quality Engineer.
- Metadata and lineage: Ensure that pipelines publish metadata and lineage to Microsoft Purview.
- Orchestration and automation: Implement scheduling, dependency management, parameterization, error handling, and alerting.
- Performance and cost: Optimize pipelines, partitioning, file formats (Delta/Parquet), and compute usage for performance and cost efficiency.
- Security: Apply access controls, masking, encryption, and secure credential management in line with UAE PDPL, the Dubai Data Law, and DESC ISR.
- DevOps / DataOps: Maintain code in source control and deploy through CI/CD pipelines, with automated tests and environment promotion.
- Operations and knowledge transfer: Support production operations, incident resolution and runbooks, and coach Client's engineers so that the pipelines can be sustained after handover.
Qualifications and Experience
- 4+ years in data engineering, preferably within UAE government or regulated-sector environments.
- Advanced SQL, Python, and PySpark/Spark skills.
- Hands-on experience with Azure Data Factory, Microsoft Fabric, Databricks, or Synapse.
- Strong understanding of Lakehouse/Medallion architecture, Delta/Parquet formats, and dimensional modelling, including SCDs and surrogate keys.
- Experience with CI/CD (Azure DevOps or GitHub), source control, and DataOps practices.
- Familiarity with Microsoft Purview metadata and lineage, and with DQ tooling.
- Awareness of UAE data regulation, including UAE PDPL, the Dubai Data Law, and DESC ISR.
- Excellent English communication and documentation skills; Arabic proficiency is an advantage.
