During my internship, I built production-minded data pipelines for internal partners in Wells Fargo’s Commercial and Corporate Investment Banking division.
The work strengthened my approach to data quality and repeatable automation: each workflow had to move a large volume of records while producing outputs that downstream teams could use with confidence.
Selected impact
- Engineered four end-to-end Python ETL pipelines processing more than 400,000 entries each week from internal SQL databases.
- Developed batch scripts that automated extraction, transformation, and loading into target tables and generated files.
- Supported proofs of concept by cleaning, processing, and formatting data for business partners.