Fannie Mae ETL Automation Enterprise financial data moving through AWS at volume, with ETL that had become slow and hard to trace. The work automated those workflows across Glue, Lambda, S3, EMR and Athena, rebuilt the Python applications running them, and tuned SQL and PostgreSQL so processing held steady under load. Operational performance improved 30%. Every process step was documented, which mattered day to day as much as the speed gain, since recurring issues could then be resolved without re-tracing the whole pipeline. The result is a dependable data foundation that downstream reporting and analytics read from directly.