I have one excel file that must land in Snowflake through a repeatable Python ETL. The script should open each file, apply a clear set of transformations I will provide (mostly cleaning, a bit of aggregation and row-level filtering), then load the final dataset into a target table in my Snowflake warehouse. I’ll share a small sample file and the desired table schema so you can map columns, cast data types and add any calculated fields before the load. The solution has to run headlessly on a Linux box, so please rely on standard libraries—pandas, openpyxl or xlrd for reading Excel, and the official snowflake-connector-python for the load. Connection parameters, file paths and table names need to be externalised in a simple config file or environment variables for easy reuse in production. Deliverables • A clean, well-commented Python script (or notebook converted to .py) that performs the entire flow end-to-end • A short README explaining dependencies, setup steps and how to trigger the job with different input files • A quick log of your test run showing rows read, transformed and inserted/updated in Snowflake I will validate by running the script on my own machine, reviewing the logs and checking record counts in Snowflake. If everything aligns, the job is done.