Uber Software Engineer Interview Questions

I would keep the design simple until there is a clear reason to generalize it. Extra abstraction can help scale, but it can also make the system harder to understand and change. The best answer shows judgment about when complexity is worth it.

I would use a min-heap of size K so I only keep the most relevant items as the stream grows. That gives efficient updates without storing everything in memory. A strong answer explains why the structure fits the input pattern.

I would define which event is authoritative, how late updates are handled, and whether conflicts can be merged safely. Then I would design the system so users do not see inconsistent results for long. Good state handling is about correctness under messy real-world timing.

I would separate ingestion from processing, make retries safe, and ensure each stage can recover from failure without losing data. Then I would add monitoring so lag, duplicate processing, and dropped events are visible quickly. Reliability comes from designing for failure, not hoping it does not happen.

I would compare the affected group with the healthy group and look for differences in configuration, traffic, data, or environment. Then I would narrow the issue by isolating the smallest pattern that reproduces it. That kind of debugging depends on careful comparison and disciplined observation.