DaniyalAneeq/ecommerce-datapipeline-orchestrated-with-airflow — reverse-engineered prompt

Build me an end to end batch data pipeline project for ecommerce data.

I want CSV order and customer files to land in AWS S3, get moved through landing, processing, and processed folders, then load into Snowflake raw tables. After that, create a reporting table that joins customers with orders and shows total order value by customer and date. Orchestrate the whole thing with Airflow as one DAG that can run on local Airflow or Amazon MWAA.

Please include sample CSV data, environment config examples, Snowflake setup SQL, and clear docs for setting up S3, Kinesis Firehose, IAM, Snowflake stages, and the Airflow Snowflake connection. The DAG should use a batch id for each run so files and rows are traceable and rerunnable without confusion.

Keep credentials out of git, add sensible gitignore rules, and make the README easy enough that someone can clone the repo, fill in config, provision AWS and Snowflake, deploy the DAG, and trigger a test run.