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Disney·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say
Jun 2026

Summary

System design round at Disney for a software engineering role. The whole thing was basically one big question about building a Twitter-style platform from scratch, and it went pretty deep across a lot of areas I wasn't equally prepared for.

Questions Asked (1)

Q1

Design a Twitter-like social platform. Walk through the data model, core user interactions, feed generation, storage strategy, search and trending, and how you'd scale the whole thing to hundreds of millions of users.

System DesignData ModelingTechnical Trade-offs
Author's notes

This was a single question that ate the entire session.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale (e.g., 300M MAU, read-heavy, eventual consistency acceptable). Then walk through the design in layers: data model, core interactions, feed generation, storage, search/trending, and scaling. Emphasize trade-offs and justify choices based on Twitter-like constraints.

Pro tip: Anchor the discussion on the read-heavy nature (100:1 read:write) and how that drives precomputation (fan-out on write) for feeds, while acknowledging the need for a hybrid approach for celebrities. This shows you understand real-world trade-offs.

1. Clarify Requirements and Scale

Ask about expected scale (users, tweets/day), read/write ratio, latency requirements, and consistency needs. Establish assumptions to guide design.

2. Design Data Model and Core Interactions

Define entities (User, Tweet, Follow, Like, etc.) and their relationships. Describe core interactions: posting, following, timeline viewing, and engagement.

3. Feed Generation and Storage Strategy

Explain feed generation (push vs. pull vs. hybrid) and storage choices (SQL vs. NoSQL, caching, blob storage for media). Justify based on access patterns.

4. Search and Trending

Outline how to index tweets for search (e.g., inverted index, Elasticsearch) and compute trending topics (e.g., sliding window, count-min sketch).

5. Scaling to Hundreds of Millions

Discuss horizontal scaling, sharding, replication, caching, CDN, and async processing. Address bottlenecks and trade-offs.

Key Points to Mention

  • Fan-out on write vs. fan-out on read and hybrid approach for celebrities
  • Sharding strategies (e.g., by user ID, tweet ID) and consistent hashing
  • Caching layers (Redis/Memcached) for timelines and hot data
  • Use of NoSQL (Cassandra) for tweets and graph DB for social graph
  • Search indexing with inverted index and trending with streaming analytics
  • Trade-offs: consistency vs. availability, latency vs. cost, and CAP theorem

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