In January 2025, J.M. Schmid developed an end-to-end temperature data ingestion pipeline for the data-hydenv/data repository, focusing on time-series analytics. Schmid engineered the integration of two new CSV data sources, one providing 10-minute interval temperature readings and another offering hourly temperature and origin data. Leveraging data engineering skills, Schmid ensured seamless ingestion and traceable integration into existing analytics pipelines, supporting granular trend analysis and downstream forecasting. The work, tracked through reproducible commits, established a robust foundation for enhanced monitoring and data-driven decision-making. Schmid’s contribution demonstrated depth in data pipeline design and practical application of CSV-based data engineering techniques.