At The Modern Data Company, I led and mentored a team of five Data Engineers adopting Databricks Lakehouse architectures. I optimized Spark and Databricks ETL workflows, cutting job execution time by 40% and cloud compute spend by 30%.
I architected Delta Lake and Apache Iceberg-backed Medallion architectures, improving Databricks SQL query performance by 4x and reducing S3 storage costs by 30%. I also implemented Unity Catalog for centralized access control, discovery, and lineage.
I built self-service data products with FastAPI and Streamlit that reduced ad-hoc data requests by 60%, and designed custom MCP tools to make data products accessible to over 100 users. I also deployed Apache Superset on Kubernetes for self-service BI.
Previously, as an Analytics Engineer at The Modern Data Company, I developed an automation tool that boosted engineering productivity by 50% and built streaming data pipelines. I implemented data quality checks with Amazon Deequ and SODA, contributing to 99.9% pipeline reliability.
