Developed and delivered two environmental time-series datasets for the data-hydenv/data repository, focusing on enabling analytics and machine learning workflows. The work involved collecting and engineering data into ready-to-use CSV files, including a 10-minute interval dataset with ID, timestamp, temperature, and lux, as well as an hourly temperature dataset with explicit origin indicators. By emphasizing data provenance and clear timestamping, the approach improved governance and auditability while reducing preparation time for downstream users. Leveraging skills in data collection and data engineering, the developer established a foundation for scalable, reproducible time-series assets to support historical analysis and model development.