Description

Design and develop scalable ETL/ELT pipelines using Databricks including Delta Lake, Auto Loader, and DLT.
Develop batch, streaming, and CDC ingestion pipelines to enable efficient and near real-time data processing.
Prior experience with data migration from various data sources like Redshift, DB2, Oracle, Mysql, PLSSql in to databricks Implement ingestion patterns using Auto Loader with checkpointing and schema evolution for structured and semi-structured data Develop and maintain reusable DBX functions for data transformation, data quality checks, and validation logic, ensuring consistent implementation across DLT and notebook-based pipelines.
Leverage Unity Catalog to establish secure data governance, enabling controlled access, lineage tracking, and management of External Locations and Volumes across workspaces.
Partner with cross-functional teams to enable secure data sharing using Delta Sharing across internal domains and external partners.
Integrate Power BI/Tableau/Looker with Databricks using optimized connectors (ODBC/JDBC) and Unity Catalog security controls Implement Medallion architecture (Bronze, Silver, Gold layers).
Develop incremental and CDC-based ingestion pipelines Design and implement real-time streaming pipelines using Kafka and Structured Streaming.
Optimize Spark jobs, SQL queries, and streaming pipelines.
Strong SQL and data modeling skills.
Experience with cloud platforms and distributed systems.
Build, package, and deploy Databricks data pipelines using Databricks Asset Bundles (DAB), with automated CI/CD processes managed through GitHub or GitLab

Key Skills

Education

Bachelor's degree