Databricks - Lead Data Engineer - Bangalore/Chennai/Pune

Job description

• Role Overview Engineering lead who owns design & delivery end-to-end; raises bar on performance, DataOps, and governance; mentors C3s. • Core Responsibilities • Design high-throughput batch & streaming (Structured Streaming/Autoloader) to Medallion targets. • Implement advanced Delta: MERGE/SCD2, schema evolution/enforcement, OPTIMIZE/Z-ORDER/VACUUM, compaction. • Engineer observability: metrics, alerts, SLIs/SLOs, error budgets; on-call runbooks. • Implement Unity Catalog patterns (RBAC/ABAC), row/column-level security; Key Vault integration; PII/PHI handling. • Own cost & performance: Photon, autoscaling, cluster policies/pools; job SLAs. • Lead CI/CD (Repos/CLI/ADO) with automated unit/data tests and promotion gates; design reviews and reusable frameworks. • Must-have Skills (Screening Focus) • Deep PySpark/Spark SQL/Delta; DLT + Workflows orchestration. • MERGE/SCD2; schema evolution/enforcement; time travel. • Performance/cost levers: OPTIMIZE/Z-ORDER, file sizing, Photon, autoscaling; cluster policies/pools. • Unity Catalog RBAC/ABAC; secrets; PII/PHI controls. • CI/CD with tests (unit/data expectations) and environment promotion; on-call readiness. • Nice-to-have (Prefer, not Mandatory) • Kafka/Event Hubs streaming patterns; Synapse integration. • Delta Sharing, Lakehouse Federation; dbt for transformations. • 90-day Outcomes (Examples) • Reduce a priority jobs runtime 25% and cost/GB 20% within 90 days. • Stand up CI/CD + tests + SLOs for one DLT pipeline with alerting; publish a reusable SCD2/DQ module.