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Extract and clean a usable dataset from a messy real-world database using SQL plus Python (dedupe, types, nulls, joins, validation).

The applied data-wrangling screen: here is a grubby database, produce a clean analysis-ready table. The signal is profiling before transforming, doing set-based cleaning in SQL and row-level fixes in Python, joining without fanning out rows, and validating the output instead of trusting it.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

The applied data-wrangling screen: here is a grubby database, produce a clean analysis-ready table. The signal is profiling before transforming, doing set-based cleaning in SQL and row-level fixes in Python, joining without fanning out rows, and validating the output instead of trusting it.

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