Design the event instrumentation for Safety Toolkit at scale

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’s Safety Toolkit is a critical in-trip experience that gives riders access to safety-related actions such as contacting emergency support, sharing trip status, reporting concerns, or accessing trusted safety resources. In this interview, you are asked to design the event instrumentation for this toolkit at scale, across a global marketplace with varied device quality, network reliability, local safety regulations, and user familiarity with app-based mobility services.

Focus on how Uber should capture meaningful, reliable, and privacy-conscious data about how price-sensitive riders discover, open, use, and complete Safety Toolkit actions during rides. The instrumentation should help product, engineering, safety operations, data science, and regional teams understand whether the toolkit is accessible, trusted, performant, and effective without creating unnecessary user risk or collecting inappropriate sensitive information.

You are not being asked to redesign the Safety Toolkit itself. The scope is to define what should be instrumented, how events should be structured, what data contracts and system requirements are needed, and how the instrumentation can support analysis, alerting, experimentation, compliance, and operational response at Uber scale.

The experience should consider:

- Key user workflows before, during, and after a trip where Safety Toolkit exposure or usage may occur

- Event taxonomy, naming, properties, session/trip linkage, timestamps, and consistent client/server-side logging

- APIs, data pipelines, schemas, versioning, deduplication, latency expectations, and failure handling

- Privacy, security, data minimization, retention, access controls, and handling of sensitive safety-related signals

- Reliability across low-end devices, poor connectivity, international markets, and multiple app versions

- Instrumentation for cohorts such as price-sensitive users, first-time riders, shared rides, late-night trips, geographies, and incident-prone contexts

- Observability, anomaly detection, dashboards, alerts, and operational handoffs when safety-related events indicate potential risk

- Product trade-offs between analytical completeness, performance overhead, user trust, regulatory complexity, and engineering maintainability

The goal is to evaluate how you translate a high-stakes product surface into a scalable technical instrumentation plan that enables decision-making, protects users, supports safety operations, and remains reliable across Uber’s global ride marketplace.