astronomer/airflow-data-quality-demo ? reverse-engineered prompt

Build me an Airflow demo project that shows different ways to check data quality and data integrity in real workflows.

I want a local setup I can run with Astronomer and Docker, with example DAGs under a dags folder for a few common backends like SQL, BigQuery, Redshift, Snowflake, Firebolt, and Great Expectations based checks. The goal is to make it easy to open Airflow locally, set the needed connections and variables, and then run through the sample workflows to see how the checks work.

Please include clear example code, sensible folder organization, and any helper files needed for SQL examples or Great Expectations configs. If something depends on cloud credentials or a database being available, make that obvious in the README or comments. Keep it simple enough that someone can clone it, start it up, and follow along without guessing too much. If you need to look up current docs online, go ahead.