Lead Data Engineer (Databricks)

THE ROLE

You are the senior (7-8 years of experience required), hands-on engineer who leads the design and build of Databricks lakehouses for our clients setting platform standards, delivering the medallion and governance layers, and mentoring the team. You work under the Principal Architect and are the technical anchor on your accounts.

WHAT YOU'LL DO

• Design and build end-to-end lakehouse solutions on Databricks, bronze/silver/gold medallion across client engagements.

• Stand up and govern Unity Catalog (access, lineage, PII masking) and CI/CD with Databricks Asset Bundles, Git, and Workflows / Lakeflow.

• Build ingestion pipelines from enterprise sources (Salesforce, QuickBooks/Accounting Seed, UKG, T&E systems, files) via Lakeflow Connect, Auto Loader, ADF or AWS Glue, or partner connectors — using Lakehouse Federation for fast interim delivery while pipelines mature.

• Optimize Spark / Delta pipelines for performance and cost (serverless, right-sizing, cluster policies).

• Partner with analytics engineers to expose gold models to Power BI and Genie.

• Act as a client-facing technical lead: translate requirements into architecture and present to US stakeholders.

• Set and document engineering standards; mentor junior engineers; contribute to reusable SLD

accelerators.

WHAT YOU'LL BRING

• 7+ years in data engineering, including 3+ hands-on with Databricks in production.

• Deep Spark / PySpark, advanced SQL, and Delta Lake; fluent in medallion architecture.

• Hands-on Unity Catalog, Databricks Workflows / Lakeflow, Asset Bundles, and Git-based CI/CD.

• Strong cloud experience on Azure or AWS (either is fine, Databricks runs on both); Infrastructure-as-Code (Terraform) a strong plus.

• Proven end-to-end implementations and client-facing / consulting experience (US-client exposure a plus).

• Excellent English communication; comfort with ambiguity and multiple concurrent engagements.

• Based in India and willing to overlap with US business hours.

BONUS POINTS

• Databricks certification required, Databricks Certified Data Engineer Professional is ideal

• Azure (DP-700) or AWS data / solutions-architect certs also a plus.

• Experience with Salesforce / QuickBooks / UKG data or PE portfolio-company reporting.

• Exposure to Mosaic AI or GenAI data workflows.