At Paltech, I lead hands-on engineering across data migration and modernization, and review data-platform architectures through the Center of Excellence. I’ve audited five projects and created Apache Spark learning material that helped train more than 20 engineers.
On Wizard AI, I lead a three-engineer team modernizing a retail data platform on GCP Dataproc, Spark and Airflow. We expanded retailer coverage from 300 to 955 and reduced pipeline runtime from about 17 hours to about four, while configuration-driven orchestration reduced run costs from about $500 to $114.
Previously at Tata Consultancy Services, I developed Azure Data Factory pipelines for a retail migration from private to public cloud, preparing data for inventory operations and Blue Yonder forecasting. I also contributed to Databricks migration work, healthcare data architecture and an agentic SQL Server-to-Databricks migration framework.
