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

SeniorPrefer not to say
May 2026

Summary

Got a system design question at Wealthfront that was pretty much just 'design YouTube.' No frills, no extra context, just that.

Questions Asked (1)

Q1

Design YouTube.

System DesignTechnical Trade-offsAPI & Integrations
Author's notes

Classic open-ended system design.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the scope and core requirements of a YouTube-like system, focusing on video upload, storage, streaming, and metadata. Then propose a high-level architecture that addresses scalability, reliability, and trade-offs, and dive into one or two components in depth. Finally, discuss how the design would integrate with Wealthfront's existing systems or financial data pipelines.

Pro tip: Emphasize the trade-offs between consistency and availability, especially for view counts and recommendations, and how eventual consistency can be acceptable. Also, mention cost optimization strategies for storage and CDN, as Wealthfront values engineering efficiency.

1. Clarify Requirements and Scope

Ask questions to define functional and non-functional requirements, such as scale, latency, and key features (upload, streaming, search, recommendations).

2. High-Level Architecture

Outline the main components: client, API gateway, video processing service, storage (blob and metadata), CDN, and recommendation engine. Explain data flow from upload to playback.

3. Deep Dive into Critical Components

Choose 1-2 components (e.g., video transcoding pipeline or CDN caching) to detail, discussing technologies, scaling strategies, and trade-offs.

4. Address Scalability and Reliability

Discuss how to handle massive scale: sharding, replication, load balancing, and fault tolerance. Mention monitoring and alerting.

5. Integration and Trade-offs

Explain how this system could integrate with Wealthfront's ecosystem (e.g., secure video for financial advice) and discuss trade-offs like cost vs. performance, consistency vs. availability.

Key Points to Mention

  • Video transcoding and adaptive bitrate streaming (e.g., HLS, DASH) for varied network conditions.
  • Storage tiering: hot vs. cold storage for popular vs. long-tail videos, using object stores like S3 and CDN for delivery.
  • Metadata management: using a scalable database (e.g., Cassandra, DynamoDB) for video metadata and user data.
  • Recommendation system: leveraging user behavior and machine learning, with eventual consistency for view counts.
  • API design: RESTful or GraphQL endpoints for upload, search, and playback, with authentication and rate limiting.
  • Security and compliance: DRM, encryption, and access controls, especially for financial content.

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