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Walmart Labs·Technical Product Manager·Onsite - System Design / Architecture·Senior

Senior
May 2026

Summary

TPM interview at Walmart Labs that centered on a system design question about building something at the scale of Google Play Store. Pretty technical for a TPM round, which surprised me a bit.

Questions Asked (1)

Q1

Walk through how you would design Google Play Store from scratch, covering database choices, schema structure, and why you made those calls.

System DesignData ModelingTechnical Trade-offs
Author's notes

This one took me a second to scope properly.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale (e.g., number of users, apps, downloads) to frame the design. Then propose a high-level architecture, focusing on database choices and schema for core entities like apps, users, reviews, and transactions. Justify each decision with trade-offs around consistency, availability, and scalability.

Pro tip: Emphasize that as a TPM, your role is to balance technical feasibility with business goals—highlight how your database choices directly impact key metrics like app discovery, download speed, and developer satisfaction.

1. Clarify Requirements and Scale

Ask questions to understand expected scale (e.g., billions of users, millions of apps), key features (search, recommendations, reviews, payments), and non-functional requirements (latency, consistency).

2. High-Level Architecture

Outline major components: client apps, API gateway, microservices (app catalog, user management, reviews, payments), and data stores. Explain how they interact.

3. Database Choices

Select databases for different needs: e.g., Cassandra for app metadata (high write throughput, availability), Redis for caching, Elasticsearch for search, and a relational DB for transactions. Justify each based on CAP theorem and access patterns.

4. Schema Design

Propose schemas for core entities: apps, users, reviews, downloads, and transactions. Discuss normalization vs. denormalization, indexing, and partitioning strategies.

5. Trade-offs and Scalability

Discuss trade-offs (e.g., eventual consistency vs. strong consistency), scaling strategies (sharding, replication), and how to handle growth and failures.

Key Points to Mention

  • Use of polyglot persistence: different databases for different use cases (e.g., Cassandra for app catalog, Redis for session/cache, Elasticsearch for search).
  • Schema design for apps: include fields like app_id, name, developer, category, ratings, download_count, and version history; consider denormalization for read-heavy access.
  • Handling reviews and ratings: use a time-series or wide-column store for scalability, with aggregation for average ratings.
  • Transaction management for payments: ACID compliance with a relational database or distributed transaction patterns.
  • Caching strategy: CDN for static assets, Redis for frequently accessed data to reduce latency.
  • Sharding and replication: partition data by app category or user region to distribute load and ensure availability.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.