Clinical Data Engineering Lead

Own data-engineering delivery on Google Cloud Platform/DataFlow, including ingestion, transformation, standardisation, reconciliation, publication and operational engineering standards., Define reusable DataFlow/Google Cloud Platform ingestion and transformation patterns.

• Implement source ingestion from Epic, ELMS, Oracle, terminology and other approved sources.
• Build raw/source-preserving, standardised/cleansed and curated/mastered processing layers.
• Implement standardisation, validation, transformation and reference-data enrichment.
• Build reconciliation controls between source, MDM/RDM and downstream publication.
• Build publication pipelines to Google Cloud Platform data products, APIs, events and tables/files.
• Implement replay, restart, idempotency, audit and monitoring; optimise performance and cost.
• Establish CI/CD, code quality and production support procedures.

Primary Deliverables

• Data engineering architecture / design
• Ingestion and transformation pipelines
• Reconciliation framework
• Publication pipelines
• Operational monitoring and runbooks
• CI/CD and engineering standards

8+ years in data engineering, hands-on with Google Cloud Platform and DataFlow (or equivalent).

• Large-scale batch, incremental and event-driven pipeline experience.
• Experience feeding and reconciling MDM/RDM data.
• Strong on operationalisation: monitoring, replay, CI/CD.