AWS Athena lets you run SQL queries directly on S3 data (JSON, Parquet, CSV, ORC) without provisioning data warehouses. You write ANSI SQL, Athena parallelizes across S3 files, returns results in seconds. Mastery means designing table schemas for queryability, optimizing for query costs (partitioning, compression, column selection), and integrating Athena into analytics pipelines. Learning path: SQL fundamentals (2 weeks) → Athena setup (1 week) → query optimization (2 weeks) → cost optimization (1 week) → integration patterns (2 weeks).
AWS Athena is a query service that lets you analyze data stored in S3 using standard SQL. No servers, no ETL pipelines, no infrastructure to manage. You upload data to S3, define a table schema (or use Glue to auto-detect it), write SQL, and Athena parallelizes the query across S3 files and returns results. You pay per byte scanned, not per hour. Athena is powered by Apache Presto, which means you write real ANSI SQL. It's ideal for data scientists, analysts, and engineers who need fast ad-hoc queries without the overhead of a data warehouse.
| 지역 | 주니어 | 미들 | 시니어 |
|---|---|---|---|
| USA | $70k | $115k | $160k |
| UK | £42k | £70k | £105k |
| EU | €48k | €75k | €115k |
| CANADA | C$75k | C$120k | C$165k |
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