Tell me about your experience with AWS data services more broadly. Have you worked with Athena, and how do you decide when to use Athena versus Redshift for querying?

Athena is a serverless, pay‑per‑query service that reads data directly from S3 using Presto. It’s ideal for ad‑hoc analytics, quick exploratory queries, or when you don’t want to manage a cluster. Redshift, on the other hand, is a managed columnar data warehouse that requires provisioning a cluster but offers higher performance for large, structured workloads, complex joins, and concurrent users. I choose Athena when the dataset is relatively small, the query pattern is unpredictable, or cost control is paramount. I opt for Redshift when the data volume is large, the schema is stable, you need low‑latency reporting, or you’re running heavy OLAP workloads that benefit from vacuuming, sort keys, and distribution styles. In practice, I often start with Athena for quick insights and migrate to Redshift once the data model matures and query performance becomes critical.