Welcome to your interview.
The question is on your right: Time Series Feature Engineering. Take a moment with it first.
Talk your thinking through with me if you like - when you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes). Discussion and graded submissions share your five interviewer interactions, so spend them well.
You are working on a forecasting task where past values, seasonality, and recent trends all matter. The raw data is noisy, irregular in places, and the useful signal is spread across time.
How would you approach feature engineering for a time series forecasting problem?