Description
The role leads the design and implementation of scalable Databricks Lakehouse data solutions for analytics and business applications. Responsibilities include building high-volume batch and near-real-time pipelines with PySpark, SQL, Python, Delta Lake, and Databricks workflows; developing CDC, incremental, deduplication, SCD, and schema-evolution frameworks; designing reusable data models; supporting governance, security, lineage, and production operations; mentoring engineers; and collaborating with data architects, analysts, BI teams, data scientists, and business stakeholders. The role requires strong Python, SQL, Spark, Databricks, and Delta Lake experience, along with knowledge of orchestration, infrastructure-as-code, data observability, cloud-native technologies, and AI/GenAI data platforms.
