Your question is Cleaning Nulls and Duplicate Records. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
In data engineering work, raw source data often arrives with missing values, repeated rows, and inconsistent text or date formats. In PwC data transformation workflows, these issues directly affect reporting quality and downstream trust.
Explain how you handle nulls, duplicates, and inconsistent formats during SQL transformations. Your answer should cover how you detect each issue, how you decide whether to keep, replace, or remove problematic values, and which PostgreSQL techniques you would use to standardize the data.
Keep your answer practical rather than theoretical. The interviewer is looking for a clear transformation approach, common SQL functions such as COALESCE, CASE, TRIM, LOWER, and casting/parsing functions, plus how you think about data quality and data integrity when preparing data for analytics.