At Thorogood Associates, I architected a multi-agent system using Agent Bricks to route natural-language questions across Databricks Genie spaces. I also developed an AI-assisted framework that converts Alteryx workflows into Databricks-compatible PySpark, reducing migration turnaround time by 50%.
For an enterprise forecasting engine, I collaborated on a metadata-driven ETL and orchestration framework in Databricks that cut cycle runtime from 3–4 man-days to 4 hours across 14 international markets. I also engineered configuration-based onboarding across 40M+ rows and 45+ financial KPIs.
I built PySpark ingestion pipelines that standardize irregular date headers, and a multithreaded data-quality engine that validates files and quarantines corrupt loads. My Azure Data Factory and Databricks pipelines used Medallion architecture and SCD Type 2 logic to track changes across 10M+ records and reduce reporting turnaround time by 30%.
I also delivered Power BI dashboards integrated with PowerApps, SQL stored procedures, and semantic models, reducing manual Excel work by 80%. My work spans data engineering and applied AI, supported by Databricks certifications in Generative AI Engineering and Data Engineering.
