Hands‑on Fabric engineer with significant experience across Fabric data ETL. Makes informed choices between Fabric components (e.g., Lakehouse vs Warehouse; Pipelines, Dataflow, Mirroring, Shortcuts) based on real‑world constraints. Strong SQL/T‑SQL; able to rewrite Qlik load scripts into Fabric SQL/T‑SQL, simplifying and optimising them for Lake-house/Warehouse. Will work alongside data analysts and developers to migrate E2E Qlik reports into Fabric and Power BI, will need to coach and upskill analysts and developers and document approach, process and best practice.
Core Experience (Must‑Have)
- End‑to‑end Fabric delivery specifically across storage, ingestion, and ETL in production.
- Fabric decision‑making: practical choices between Lake-house vs Warehouse, and use of Pipelines, Dataflow, Mirroring, Shortcuts based on real constraints.
- Pipelines: set up and run Fabric Pipelines for ETL/ELT (ingestion, orchestration/scheduling) with production‑grade alerting and monitoring.
- Strong SQL incl. T‑SQL for transformations and optimisation.
- Qlik → Fabric: able to rewrite Qlik load scripts into Fabric SQL/T‑SQL, simplifying and optimising logic for Lake-house/Warehouse execution.
- Power BI: comfortable building reports on Fabric datasets.
- Enablement & documentation: partner with technical teams, provide Fabric and Power BI advise and support, and document processes/decisions.
Responsibilities (Overview)
- Lead design and build of Fabric ETL aligned to team needs and best practice.
- Select and justify Fabric components and their trade‑offs.
- Migrate and optimise Qlik logic to Fabric SQL/T‑SQL for efficient execution.
- Coach analysts/developers and document architecture and runbooks.
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