Senior Data Engineer at CVS Health

Spearheaded scalable data pipelines using AWS and Python, improving data processing efficiency by 30% and enhancing analytics data accessibility. Optimized SQL and leveraged Snowflake for warehousing, reducing query execution times by 25% and improving downstream performance. Designed and implemented robust CDC mechanisms to ensure timely updates and historical accuracy in data lakes. Developed and maintained Databricks data models using Medallion Architecture to streamline ingestion and processing across projects. Implemented governance with Unity Catalog, automated data validation and monitoring, and led Agile delivery with Git-based CI/CD improvements. Performed performance tuning to reduce operational costs by 20% and mentored junior engineers in data modeling and pipeline best practices.

Advanced Data Engineer at JPMorgan Chase

Engineered and maintained high-performance ETL/ELT pipelines using Azure and Spark, improving processing speeds by 40% and enabling real-time analytics. Designed and implemented SCD architectures in Delta Lake for correct historical representation and business compliance. Partnered with analysts and dashboard developers to gather requirements and create reusable semantic data models as a single source of truth. Investigated source systems to improve extraction quality, built automated data quality monitoring with Databricks, and established governance for access control and compliance. Implemented data lineage tracking for audit support and applied Agile practices to improve team delivery. Optimized database performance via indexing and query tuning, reducing execution times by 30%.