Uber Software Engineer Mock Interview

Tell me about a time you had to improve reliability or latency for a production system at scale—what was the incident or bottleneck, how did you diagnose it, and what measurable changes did you make (and how did you validate them)?

Uber relies on high-throughput services and data pipelines—walk me through how you would design an event-driven pipeline to power real-time trip status updates, including how you’d handle retries, deduplication, ordering, and backpressure.

Describe a situation where you had to make a trade-off between shipping quickly and building the “right” solution—how did you decide, what constraints (team, product impact, safety) mattered most at Uber, and what was the outcome?

Imagine you’re working on fraud prevention for Uber’s marketplace: given a new suspicious pattern, how would you approach feature definition, model evaluation, and safe rollout to reduce false positives without harming legitimate riders/drivers?

You’re asked to implement a feature for Uber that must work globally across multiple regions with different data availability and latency characteristics—what strategy would you use for API design, consistency, and testing to ensure correctness and performance under real-world conditions?