May 2026 — HPDP: Delivered the Data Processing Pipeline Refactor in drshahizan/HPDP, removing the legacy data cleaning notebook and shifting the data processing workflow toward a modern approach for job data. This change reduces maintenance overhead, standardizes data handling, and lays the groundwork for improved throughput and easier future enhancements. The work was completed around a single focused commit (44ca7510702ab030094cfa669352905327a915a0). There were no documented critical bugs fixed this month; the refactor addresses key reliability and maintainability pain points associated with the legacy notebook. Overall, this work improves data quality, reproducibility, and scalability of the HPDP data pipeline, enabling faster iterations and clearer ownership of the pipeline stages. Technologies demonstrated include Python-based data engineering, pipeline design, notebook-to-pipeline migration, and strong version control practices.