Quant SQL Interview Guide
Quant SQL interview guide for schema reading, filters, joins, groupby, window functions, debugging, examples, and data checks.
Candidates practicing data querying for research or trading contexts.
Start by reading the schema
Before writing SQL, identify the table grain, primary keys if known, timestamp columns, and what each row represents. This prevents many join and aggregation errors.
Build queries in stages
Complex quant SQL is easier when staged: filter the data, join carefully, aggregate at the intended grain, then compute final metrics.
Concrete example
To compute daily traded volume by symbol, first confirm each row is a trade or fill, then group by date and symbol and sum quantity.
Use windows for row-aware metrics
Lag, rank, row number, and rolling calculations often need window functions. Always specify partition and order before interpreting results.
Common mistakes
Candidates often write one large query and hope it works. Smaller CTEs with checks are easier to debug, explain, and revise.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.