Senior Data Engineer

Technical Responsibilities

• Data Modelling: Design and maintain scalable, enterprise-grade dimensional models (star/snowflake schemas) that map business processes to analytics.
• Pipeline Engineering: Build and optimize batch, incremental, and CDC pipelines using Spark/PySpark across Databricks and Microsoft Fabric ecosystems.
• Advanced SQL & Integration: Write and tune complex, production-grade SQL for data transformations across Warehouse and Lakehouse endpoints.
• Platform Governance: Manage data environments using Delta Lake, Unity Catalog, and Microsoft Fabric tools (OneLake, Data Factory, Dataflows).
• Quality & Documentation: Implement automated CI/CD data quality checks, maintain data lineages, and tag metadata for discoverability.
• Optimization & FinOps: Profile query performance and apply FinOps principles to minimize cloud compute and resource costs.

Key Requirements & Soft Skills

• Priority Management: Ability to manage competing delivery demands, assess urgency, and adapt to shifting workloads.
• Root Cause Analysis: Methodical problem-solver who diagnoses technical issues, implements preventive fixes, and documents findings.
• End-to-End Ownership: Proactive self-starter who drives data delivery and communicates blockers without needing close supervision.
• Agile Learning: Adaptable mindset with the ability to quickly master new cloud tools, architectures, and data frameworks.