Your question is Jane Street Trading Data Pipeline. 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).
You are given a massive dataset containing daily trading volumes for thousands of assets, but some dates and values are missing or clearly corrupted. How would you design a pipeline to detect anomalies, impute the missing data, and validate your assumptions?