Data Engineer- Healthcare

🚀 Data Engineer

My client is looking for a Data Engineer to design and build scalable data pipelines that deliver trusted, analytics-ready datasets for BI, AI, and operational use cases across a hybrid environment.

Must have healthcare/healthtech experience

🔧 Key Responsibilities

• Build pipelines across bronze, silver \& gold layers (Databricks, Spark, dbt)
• Implement data quality checks, contracts \& schema validation
• Apply governance (catalog, lineage, RBAC, metadata)
• Deliver curated datasets, features \& embeddings for AI/BI
• Monitor pipeline health, performance \& cost to meet SLAs

⚙️ Tech Stack

Databricks • Spark • Delta Lake • dbt • Azure Data Factory • Kafka/Event Hubs • CI/CD (Azure DevOps/GitHub)

🔐 Governance \& Ops

• Enforce data contracts, lineage \& cataloging
• Apply masking, tokenisation \& access controls (PII/PHI)
• Build observable pipelines with alerts, dashboards \& runbooks
• Optimize performance (partitioning, caching, cost efficiency)

✅ Requirements

• 5\+ years in Data Engineering
• Strong SQL, data modeling (dimensional/data vault)
• Proficiency in Python
• Hands-on with Databricks, Spark, Delta Lake \& dbt
• Experience with Azure data services (ADF, ADLS, Key Vault)
• Familiarity with CI/CD \& container basics (Docker/Kubernetes)

➕ Nice to Have

• Streaming (Kafka/Event Hubs) \& CDC (GoldenGate)
• Catalog/lineage tools (Purview, OvalEdge)
• S3-compatible storage (MinIO, VAST)
• Exposure to BI tools (Power BI) \& healthcare standards (FHIR/MDR)

🎓 Education

Bachelor’s in Computer Science, Engineering, or related field

Only successful candidates will be contacted