Shivani Borkar

I’m a Data Engineer with 5+ years of experience designing and optimizing large-scale data pipelines, delivering scalable, cost-effective solutions for Life Sciences clients. I focus on data warehousing, performance optimization, and automation, ensuring reliable data quality and integrity end to end.

In my current role supporting eCDP Dataverse for Abbvie, USA, I build and optimize high-performance pipelines using PySpark, Python, and Apache Iceberg. I’ve delivered full and incremental ingestion workflows, tuned Spark configurations and partitioning, and improved processing speed by up to 50% through query execution refinement. I also implemented robust tracking and logging with Modak Nabu for auditing, traceability, and consistent quality, and I’ve led production deployments while resolving operational issues to ensure smooth, on-time delivery.

Previously as an ETL Tester, I developed and optimized complex Oracle SQL for extraction, transformation, and loading in a data warehouse environment. I integrated incremental load processes into ETL workflows via Informatica, validated and reconciled warehouse tables for accuracy and reliability, and improved scalable processing through indexing and execution plan optimization. I’m motivated by continuous improvement—recognized with the “Working as one Award” and ongoing client appreciations.