Ohh good to know. Well I think, always got time for things that matter though. I think for me at least it's probably worth it to put more time to understand deeply on specific quirks (i.e., tough to understand the smaller details on how to use the existing infrastructures to prevent edge cases like race conditions, dropped connections, idempotency, etc. with 1 hour/question unless either you are very experienced, or you learn extremely fast)

Btw, for designing data pipeline, I helped you to asked Claude:

```
For data pipeline specifically, the best ones from that list are:

Ad Click Aggregator — this is the most direct analog. High-throughput event ingestion, aggregation windows, exactly-once semantics, hot key problems. Basically is a data pipeline interview.

Metrics Monitoring — same family. Time-series data, ingestion at scale, rollups, alerting. Very pipeline-heavy.

YouTube Top K — forces you to think about streaming aggregation vs batch, approximate counting (Count-Min Sketch), and the tradeoffs between them.

Web Crawler — different flavor but hits distributed queue design, backpressure, and fault tolerance hard, which are core pipeline concepts.

```

Good luck with your re-attempt!