SDE2 Interview Questions at Uber

Design Uber's driver-rider matching system. How do you match the nearest available driver to a rider within 200ms at global scale? Cover: geospatial indexing (H3/S2), the dispatch algorithm, how you handle supply-demand imbalances, and what happens when a matched driver rejects the trip.

Design Uber's dynamic pricing (surge) system. When supply is low and demand is high in a geofenced zone, prices increase automatically. Explain the data pipeline, the pricing model, how you prevent oscillations (price going up → drivers rush in → price drops → drivers leave), and regulatory constraints.

Design Uber Eats' order batching system. A single delivery partner picks up orders from multiple nearby restaurants and delivers to multiple customers in one trip. How do you optimise the route and assignment?

Design Uber's payment reconciliation system. Uber collects payments in 70+ countries with different currencies, payment methods, and regulations. How do you reconcile driver payouts against rider charges and detect discrepancies?

Uber uses H3 hexagonal geospatial indexing. Explain why hexagons are better than squares or lat/lng grids for proximity searches. How do you find all drivers within 2km of a rider using H3 resolution levels?

Describe a time you had to work with a very ambiguous technical requirement. How did you clarify scope, make progress, and manage stakeholder expectations during the process?

You need to track the top 10 most active drivers by trip count, updated in real time. Which Redis data structure fits this, and why not just a plain hash with manual sorting?