Lead Data Engineer

We are seeking a Lead Data Engineer to own end-to-end data modeling and pipeline delivery as a major enterprise data lake is re-architected. You will work hands-on with Databricks and dbt, partner closely with US-based stakeholders and collaborate with an India-based engineering team. You thrive with high autonomy, clear documentation and strong ownership.

Responsibilities

Own dimensional data models from requirements through deployment using Kimball-aligned patterns Design, build and maintain pipelines in Databricks and dbt to support a modernised data lake Translate business requirements into scalable datasets, anticipating future reporting and analytics needs Lead end-to-end delivery including development, unit testing, UAT support and release coordination Produce clear technical documentation in Confluence and maintain decision records and data definitions Partner with US-based stakeholders to align outcomes, scope and delivery expectations Collaborate with an India-based engineering team to coordinate build, reviews and handovers Support basic dashboarding and validation to confirm data meets business expectations Requirements Dimensional modeling capability including star schema, fact and dimension design and aggregate awareness Hands on experience with python programming Databricks experience for data engineering development and operational support dbt (data build tool) experience including modular modelling, testing and deployment practices SQL proficiency for analytics-grade transformations and performance-aware querying Traditional ETL and data warehousing foundation adapted to modern cloud data stacks End-to-end delivery ownership across requirements, build, testing, UAT and deployment Clear communication and strong documentation habits for non-technical stakeholder engagement Self-directed working style with comfort operating under light-touch leadership Nice to have Experience re-architecting enterprise data lakes or data warehouses in multi-phase programs Familiarity with release planning across distributed teams and time zones Exposure to basic BI development or semantic layer design to support reporting consumption