Streaming windowed aggregations
Design the streaming-aggregation engine of a feature store that computes real-time windowed features ('count of logins from this account in the last 5 minutes', 'sum of transfer amounts in the trailing hour') for an account-takeover model, where these features must be correct under out-of-order and duplicate events and must read at <5ms online. Walk through the windowing and aggregation model, how you guarantee a duplicate event isn't double-counted, and how the same aggregation stays consistent between the streaming online path and the batch path used to generate training data.
Clarify scale and constraints first. Propose a clean component breakdown, then go deep on the hard parts (data model, bottlenecks, consistency, failure modes) and name the trade-offs you are making.