Key Achievements
- Enabled the university to save approximately $100K USD annually by replacing an external academic counseling platform.
- Co-implemented a risk detection system that alerts stakeholders about over 1000 critical student cases.
- Designed and implemented the unit’s complete data architecture in Databricks, following a medallion architecture and fully automating data processing and institutional information storage pipelines.
- Optimized ETL pipeline performance by 87% (reduced processing time from 15 to 2 minutes) by migrating from Pandas to Polars for data retrieval and storage from Azure Blob Storage.
- Processed academic data and developed Power BI dashboards under the guidance of Professor Marcela Hernández Hoyos, Ph.D. and Professor Juan Pablo Reyes Gómez, Ph.D., delivering actionable insights on student performance and institutional metrics.
Power BI Python Polars Azure Blob Storage Databricks SQL
