Data engineering SQL interviews are not the same as software engineering SQL interviews. You will not be asked to find the second-highest salary or reverse a string. You will be asked to sessionize user events, detect data quality issues in a pipeline, build a cohort retention table, or find consecutive streaks in time-series data. The problems are more complex, the schemas are messier, and the expectation is that you have encountered these patterns in production, not just on LeetCode.
I built these 30 problems from the SQL patterns I use repeatedly across my pipeline projects: NSE equity data, Kenyan property listings, job postings, flight data, and financial transactions. Every problem here maps to something I have written in production.
The problems use six tables throughout. Memorise the schemas before any interview:
nse_trades (trade_id, ticker, sector, trade_date, open_price,
close_price, volume, market_cap)
