Google Product Designer Case Interview (Engineering) — Systems-Scale UX, Metrics, and Material Design

This 60‑minute case mirrors how Google evaluates product designers embedded with engineering. You will tackle an ambiguous, Google‑ecosystem problem (e.g., Search, Maps, Photos, Android, or Workspace) and demonstrate user‑first, 10x thinking while balancing product, technical, and ethical constraints. What it covers at Google: - Problem framing and goals: Clarify the user problem, articulate jobs‑to‑be‑done, define primary personas and contexts (mobile, web, assistive tech), and state a crisp north‑star metric plus guardrails (privacy, safety, latency). - System‑scale solutioning: Outline information architecture, key flows, and low‑fidelity wireframes that can scale to billions of users. Show how the design degrades gracefully for low bandwidth, offline, and low‑end devices, and how it integrates with existing Google surfaces (accounts, notifications, sharing, identity). - Craft aligned to Material Design: Justify component choices, hierarchy, motion, and theming; address responsive behavior and platform conventions across Android, iOS, and web. - Accessibility and inclusion: Bake in WCAG 2.2 AA considerations (contrast, focus order, semantics, screen reader labels), internationalization and localization (including RTL), and edge cases for diverse users. - Privacy, safety, and integrity: Apply privacy‑by‑design (data minimization, consent, transparency), abuse prevention, and content/behavioral safety considerations aligned with Google policies. - Data‑informed decisions: Propose success metrics (adoption, task success, retention, satisfaction, latency), an experimentation plan (A/B or phased rollout), and instrumentation needed to validate hypotheses while protecting user data. - Trade‑offs and execution: Discuss MVP vs. V1 scoping, technical constraints surfaced by engineering (performance, reliability), and how you would collaborate with PM and Eng to sequence work via milestones and risks. Format and pacing (typical): - 0–5 min: Brief, align on problem and constraints. - 5–25 min: Problem framing, users, use cases, and success metrics. - 25–45 min: IA, flows, low‑fi sketches with rationale and trade‑offs. - 45–55 min: Metrics, experimentation, privacy/safety, rollout. - 55–60 min: Q&A and reflection on alternatives. What interviewers look for (mapped to Google expectations): - General cognitive ability: Structured thinking, clarity, and prioritization under ambiguity. - Role‑related knowledge: End‑to‑end product design craft, systems thinking, platform fluency, and Material Design literacy. - Leadership and collaboration: Proactive scoping, cross‑functional communication, and reasoned trade‑offs. - Googleyness: User empathy, humility, data‑driven decisions, and a bias toward safety and inclusion.