Siddartha Reddy Jammula

Build PySpark pipelines on Azure Databricks and Azure Data Factory processing 2 TB monthly into a Delta Lake medallion architecture. Architected a production retrieval application on Azure OpenAI and Azure AI Search over 2M+ internal documents, reducing analyst research time by 45%.

Designed and maintained production ETL/ELT pipelines in Azure Data Factory and Databricks ingesting from 50+ source systems, processing over 1 TB daily at 99.9% on-time delivery. Architected a Delta Lake lakehouse on ADLS Gen2 using a bronze/silver/gold medallion design.

Consolidated policy and claims data from 12 source systems into an Azure SQL data warehouse, building the ingestion pipelines and dimensional models behind cross line-of-business reporting. Migrated on-premises data workloads to ADLS Gen2 and Azure SQL, reducing infrastructure costs by 25%.

Built Python and SQL ETL processes for healthcare claims data, eliminating 10+ hours of manual processing per week. Tuned long-running SQL for claims reconciliation, reducing several overnight jobs to under 2 hours.

Analyzed research datasets in Python and SQL and built visualizations for university research teams. Cleaned and standardized survey data and automated recurring analyses previously performed in spreadsheets.

Wrote and optimized complex SQL with multi-table joins, window functions, and stored procedures over tables with millions of rows, cutting report generation time by 50%. Monitored scheduled ETL loads, troubleshot job failures, and reprocessed data to meet daily delivery SLAs across 3 enterprise client accounts.

Master of Science in Data Science from the University of Alabama at Birmingham from 2019 to 2020.