What API and data model would support a new Transit workflow for commuters

Problem Statement Description

Product context: Uber is a mobility and delivery platform; its products include rides, Uber Eats, grocery and retail delivery, freight, driver and courier tools, and marketplace pricing.

Uber is exploring a new Transit workflow for commuters who use a mix of public transportation, walking, and Uber rides to complete predictable daily trips. The workflow needs to help riders plan, compare, and execute commute journeys that may involve buses, trains, metro, shared mobility, and first- or last-mile Uber options.

As a Technical PM, you are expected to define the API and data model foundation that would allow Uber clients, backend services, and external transit data providers to support this experience reliably. The focus is not on visual UI design, but on the product requirements, data entities, system interactions, and trade-offs needed to make the commuter workflow usable at scale.

Your response should account for real-world constraints such as incomplete transit data, schedule changes, delays, location accuracy, pricing uncertainty, regional differences, and the need to preserve Uber’s reliability, safety, and marketplace economics.

The experience should consider:

- Core commuter use cases, including route discovery, trip comparison, real-time updates, saved commutes, and first-/last-mile ride options

- Key API surfaces needed between mobile clients, trip-planning services, transit data providers, maps, pricing, identity, payments, and notifications

- Data model entities such as stops, routes, agencies, schedules, service alerts, trip legs, fares, user preferences, and commute history

- Handling of real-time versus static transit data, including freshness, fallbacks, caching, and degraded states

- Reliability, latency, observability, and error-handling expectations for a commuter-critical workflow

- Privacy and security considerations around home/work locations, travel patterns, identity, and third-party data exchange

- Rollout considerations across cities with different transit agencies, data standards, operational maturity, and regulatory constraints

The goal is to describe a technically sound product architecture that enables a seamless commuter Transit experience while making clear product trade-offs around data quality, scalability, integration complexity, user trust, and operational readiness.