Can you tell about your S3 setup? Did you organize buckets and folders? What file format did you use? Did you use partitioning in the S3 bucket?

My S3 setup follows best practices: each environment (dev, test, prod) has its own bucket with a naming convention that includes the project name and region. Inside each bucket, I create logical folders such as raw/, processed/, and analytics/. I use a partitioned layout for processed data, e.g., processed/market=NYSE/date=2024-06-01/, which allows Athena and Spark to skip irrelevant partitions. For file formats, I store raw data as CSV or JSON for easy ingestion, and processed data as Parquet for efficient analytics. I also enable versioning on the bucket to preserve historical data and set lifecycle policies to transition older partitions to Glacier. This structure improves data organization, cost management, and query performance.