Role: Data Engineering (DE) Lead-Google Cloud Platform
Location: Rochester, Minnesota(Open for Remote)
Full Time
Experience: 8+ years
Platform Focus: Google Cloud Platform DataFlow
Role Description
Own data-engineering delivery on Google Cloud Platform/DataFlow, including ingestion, transformation, standardisation, reconciliation, publication and operational engineering standards.
Key Responsibilities
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
Required Experience & Skills:
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.
Good to Have:
BigQuery, Pub/Sub and Dataflow depth.
Healthcare data engineering.
Integration with Informatica MDM loads.
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