At House of EdTech, I scope customer requirements and translate them into end-to-end Medallion Architecture pipeline designs on Databricks, from Delta Lake ingestion and schema evolution to PySpark transformations and Gold-layer serving.
I coach professionals through hands-on Databricks pipeline labs, helping them use the Spark UI, tune AQE, and apply key-based repartitioning. These lab changes cut job runtimes by over 50%.
At Innodata Pvt. Ltd., I extracted, labeled, cleaned, and audited datasets across eight modalities, delivering 8,000+ approved tasks at 90–95% accuracy with no escalation backlog. I also used SQL and Python profiling to investigate data anomalies and authored SOPs and QC guides.
As a freelance Business Intelligence Analyst at SB&T, I engineered a Medallion pipeline consolidating sales, inventory, vendor payment, and cash-flow data. I also developed quality controls and automated reporting workflows using Python and Excel.
