Airflow workers have limited disk space. Always include a "cleanup" task or use temporary directories to delete files after processing.

You will also need to configure an in the Airflow UI (Admin > Connections) with your AWS credentials or IAM role details. Method 1: Using the S3ToGCSOperator or S3ToLocalOperator

Efficiently moving data from Amazon S3 into your workflow is a cornerstone of modern data engineering. Apache Airflow simplifies this process using dedicated operators that handle connection logic, retries, and security.

Are you moving files to a (like Snowflake or Redshift)? Are you dealing with large datasets (GBs or TBs)? Do you prefer using the TaskFlow API or Classic Operators ?

If your Airflow workers are in AWS, use VPC endpoints to avoid egress costs and speed up transfers.