- 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 setting 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.

📌 Databricks - Lead Data Engineer - Bangalore/Chennai/Pune
🏢 Happiest Minds Technologies
📍 Pune