Worked on foundational data model development and data hygiene within the data-hydenv/data repository, establishing the groundwork for reliable data ingestion and future analytics features. Focused on data management and file organization, the approach involved introducing new CSV-based data structures to support scalable pipelines while systematically removing obsolete assets to reduce repository clutter. This disciplined asset management improved maintainability and governance, ensuring a cleaner commit history and reducing risk. The work addressed both feature delivery and bug resolution, emphasizing repository organization and governance. Leveraged skills in data management and file organization, with a technical focus on CSV handling and structured data workflows.