Senior SQL is not a longer SELECT — it is scale-aware relational engineering : you can state grain , predict cardinality , read a planner , choose indexes and partitions , and reason about correctness under concurrency while keeping SQL maintainable for the next teammate. Hiring loops for senior data engineers , analytics engineers , and backend owners increasingly assume that PostgreSQL , SQL Server , Snowflake , BigQuery , or Redshift are all “just dialects” around the same invariants. The shift from junior to senior is the shift from “make this dataset” to “how does this behave at **tens or hundreds of millions * of rows, under real isolation , with observable plans?”* Below the hero, the fastest lever is still keyboard time on joins , windows , and EXPLAIN -driven refactors: Browse practice hub → , open SQL language practice → , sharpen joins → , deepen window functions → , and reinforce CTEs → .…