I need an experienced Python developer to build a fast, reliable workflow that ingests raw numerical data, performs the required cleaning and transformation steps, and then runs automatically on a schedule I can trigger or adjust at will. The end goal is a hands-off process: I drop new numeric files or pull a feed, your code detects the update, processes everything, and stores or exports the results in the agreed-upon format. Key points you should know • Scope: strictly numerical data and text involved • Automation: a lightweight orchestration approach (cron, Airflow, GitHub Actions, or similar) that fits an environment with minimal extra setup. • Quality: clear, well-commented code, straightforward configuration, and a short README so I can extend it later without chasing mysteries. Timeline The project is urgent; I’m ready to start immediately and need a working solution as soon as possible. Let me know how quickly you can deliver each phase and what you need from me upfront. What to include when you reply I’m primarily interested in your relevant experience—briefly outline past numerical-data projects or similar automations you’ve shipped, highlighting any performance wins or clever scheduling tricks. if you experienced in AWS lambda / S3 buckets etc that is an additional advantage. I’ll be available to answer questions quickly so we can move fast from day one.