Contribute hands on to the design, ETL development, and operation of cloud native data pipelines on Azure and Databricks
Design and optimize Spark based ETL frameworks for large scale batch and incremental processing
Implement complex transformations and performance tuning using Python and Spark SQL
Modernize on prem ETL workloads to Databricks/snowflake, ensuring enterprise standards for scalability, reliability, and governance
Collaborate with cross-functional teams to understand complex data requirements and deliver tailored solutions
Ensure data quality and integrity by implementing robust data validation and monitoring processes
Develop comprehensive documentation for data engineering processes and systems
Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements