Design the event instrumentation for Profiles at scale at global scale

Problem Statement Description

Product context: Netflix is a streaming entertainment company; its products include subscription video, original films and series, recommendations, profiles, games, and ad-supported plans.

Netflix Profiles are a core part of the member experience: households create separate identities for adults, kids, travelers, and shared-device users so that recommendations, viewing history, maturity controls, language preferences, games, ads experiences, and content discovery can be personalized. At global scale, the same profile workflows happen across TV, mobile, web, set-top boxes, game consoles, and partner devices, often under varying connectivity, localization, privacy, and regulatory conditions.

In this technical PM interview, you are asked to define the event instrumentation needed to understand and operate Profiles reliably at Netflix scale. The focus is not on redesigning Profiles, but on specifying what should be measured, how events should be structured, how data should flow, and how the system should support product, personalization, growth, trust, creator/content insights, and operational teams without compromising member privacy.

Your scope should include the end-to-end profile lifecycle: profile creation, selection, switching, editing, deletion, kids/maturity settings, personalization signals, cross-device continuity, account-level versus profile-level behavior, failure states, and edge cases across global markets. You should also consider how instrumentation supports experimentation, anomaly detection, data quality, compliance, and downstream analytics.

The experience should consider:

- Core user workflows and moments where profile-level events must be captured across devices and regions

- Event taxonomy, required properties, identity model, timestamps, session context, and account/profile relationships

- APIs, client/server responsibilities, offline behavior, retries, deduplication, ordering, and schema evolution

- Privacy, consent, data minimization, kids-profile protections, retention policies, and regional compliance constraints

- Reliability, latency, scale, observability, backfills, monitoring, and data quality validation

- Downstream consumers such as personalization, recommendations, experimentation, ads, games, content discovery, support, and executive reporting

- Rollout strategy, versioning, migration from legacy events, compatibility with older devices, and incident response

- Product trade-offs between richer behavioral insight, implementation complexity, member trust, and operational cost

The goal is to present a clear technical product plan for instrumentation that enables Netflix to understand profile behavior accurately and safely at global scale, while giving engineering, analytics, and product teams a dependable foundation for improving personalization, retention, discovery, and member experience.