Design the event instrumentation for Pickup at scale at global scale

Problem Statement Description

Product context: DoorDash is a local commerce and delivery platform; its products include restaurant delivery, DashPass, grocery and retail delivery, merchant tools, and dasher tools.

DoorDash Pickup serves customers who want local commerce convenience without delivery fees, while also helping merchants drive incremental demand and manage in-store handoff workflows. For price-sensitive users, the experience depends on clear pricing, accurate readiness estimates, smooth ordering, and confidence that the order will be waiting when they arrive.

In this technical PM interview, you are asked to define the event instrumentation needed to measure and operate Pickup at global scale across consumer apps, merchant systems, backend services, and marketplace operations. The scope includes capturing the end-to-end Pickup journey from discovery and menu browsing through checkout, merchant acceptance, food preparation, customer arrival, handoff, cancellation, refund, and post-order feedback.

The instrumentation design should support product analytics, experimentation, reliability monitoring, operational debugging, merchant performance insights, and marketplace health. It should account for different geographies, store types, order categories, app platforms, privacy requirements, offline or delayed merchant events, and the need for consistent definitions across teams.

The experience should consider:

- Core user and merchant workflows that must be observable across the full Pickup lifecycle

- Event taxonomy, naming conventions, required properties, timestamps, IDs, and entity relationships

- Client-side, server-side, merchant-side, and third-party integration events, including where each should be emitted

- Data quality concerns such as deduplication, ordering, latency, schema evolution, missing events, and attribution

- Metrics enabled by the instrumentation, including conversion, readiness accuracy, cancellation, wait time, defect rate, repeat usage, and merchant reliability

- Privacy, security, consent, regional compliance, and appropriate handling of location or personally identifiable data

- Observability needs for real-time alerts, experimentation, debugging, cohort analysis, and operational dashboards

- Rollout considerations for global scale, including backward compatibility, validation, monitoring, and cross-functional ownership

Your goal is to produce a clear instrumentation plan that would let DoorDash confidently understand, improve, and operate Pickup at scale without prescribing product feature changes. The focus is on requirements, data design, system reliability, trade-offs, and how the event framework enables trustworthy product and operational decisions.