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

SeniorPrefer not to say
Jun 2026

Summary

System design round at Tradedesk for a software engineer role. The main problem was a recipe management system that needed version control bolted on, which sounds manageable until you start thinking about concurrent writes and storage tradeoffs.

Questions Asked (3)

Q1

Design a Recipe Management System with add, update, delete, ingredient search, sorting, and per-user ownership. Then extend it to support full version control: every update should create a new version, track which user made the change, and expose APIs to list version history and retrieve a specific version.

System DesignData ModelingTechnical Trade-offs
Author's notes

I started with the basic CRUD schema and felt pretty good, then the version control extension came and I had to slow down.

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AI HintsAI Generated

Suggested Approach

Start by clarifying functional and non-functional requirements, then design a normalized data model with users, recipes, ingredients, and a versioning table. Walk through the core CRUD and search/sort APIs, then extend to version control by making updates append-only and exposing history and version retrieval endpoints. Discuss trade-offs like storage overhead vs. auditability and indexing strategies.

Pro tip: Emphasize that versioning should be immutable and append-only to ensure auditability and simplify concurrency; mention that you'd store a snapshot per version for simplicity, but consider diffs if storage becomes a concern.

1. Clarify Requirements and Scope

Ask about expected scale, consistency needs, and whether version history must be immutable. Confirm if search is by exact ingredient or fuzzy, and sorting criteria.

2. Design Core Data Model

Define tables: Users, Recipes, Ingredients, RecipeIngredients (many-to-many), and later RecipeVersions. Include ownership via user_id foreign key and timestamps.

3. Define APIs for CRUD, Search, and Sort

Outline REST endpoints: POST /recipes, PUT /recipes/{id}, DELETE /recipes/{id}, GET /recipes?ingredient=...&sort=... Ensure authorization checks for ownership.

4. Extend to Version Control

On every update, insert a new row into RecipeVersions with a snapshot of recipe data, version number, user_id, and timestamp. Expose GET /recipes/{id}/versions and GET /recipes/{id}/versions/{version}.

5. Discuss Trade-offs and Optimizations

Compare snapshot vs. diff storage, indexing for search (e.g., GIN on ingredient array), and caching strategies. Mention concurrency control (optimistic locking) for updates.

Key Points to Mention

  • Normalized schema with separate tables for users, recipes, ingredients, and recipe-ingredients to support efficient ingredient search.
  • Append-only versioning: each update creates a new immutable version row, preserving full history and user attribution.
  • API design: RESTful endpoints for CRUD, search by ingredient, sorting, and version history retrieval with proper authorization.
  • Indexing strategies: B-tree for sorting, GIN or full-text search for ingredient search, and composite indexes on (recipe_id, version) for version retrieval.
  • Trade-offs: snapshot per version simplifies reads but increases storage; diffs save space but complicate retrieval. Choose based on read/write ratio and storage constraints.
  • Concurrency: use optimistic locking (version number) to prevent lost updates when multiple users edit the same recipe.

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

Q2

How would you assign version IDs safely when multiple users might be editing the same recipe concurrently?

System DesignTechnical Trade-offsAlgorithms & Data Structures
Author's notes

Talked about monotonic counters at the recipe level using optimistic locking, and mentioned using a database sequence or a compare-and-swap approach.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements: are we preventing lost updates, ensuring linearizability, or just assigning unique IDs? Then propose a concurrency control mechanism such as optimistic concurrency with version numbers, and discuss trade-offs between optimistic and pessimistic approaches. Finally, address edge cases like conflict resolution and scalability.

Pro tip: Mention that version IDs should be assigned atomically with the write operation, not separately, to avoid race conditions. Also, consider using a monotonic counter or timestamp with a unique node ID to ensure global uniqueness and ordering.

1. Clarify requirements and constraints

Ask about consistency needs, expected concurrency level, and whether conflicts are common. Determine if the system requires strong consistency or can tolerate eventual consistency.

2. Choose a concurrency control strategy

Decide between optimistic (e.g., version numbers, CAS) and pessimistic (e.g., locks) approaches. Explain why optimistic is often preferred for low-contention scenarios.

3. Design version ID assignment

Propose a method to generate version IDs atomically, such as using a database sequence, a distributed counter (e.g., Snowflake), or a vector clock. Ensure IDs are unique and reflect causality.

4. Handle conflicts and retries

Describe how to detect conflicts (e.g., version mismatch) and resolve them, such as rejecting the write, merging changes, or retrying with the latest version.

5. Discuss trade-offs and scalability

Compare approaches in terms of latency, throughput, and complexity. Mention how the solution scales with multiple users and distributed systems.

Key Points to Mention

  • Optimistic concurrency control using version numbers or ETags
  • Atomic compare-and-swap (CAS) operations to update version IDs
  • Distributed ID generation techniques (e.g., Snowflake, UUIDs with timestamps)
  • Conflict detection and resolution strategies (e.g., last-write-wins, merge)
  • Trade-offs between optimistic and pessimistic locking
  • Scalability considerations in distributed systems (e.g., clock skew, network partitions)

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

Q3

Would you support branching or rollback on top of the version history, and how would that change your design?

System DesignTechnical Trade-offs
Author's notes

Framed it as optional but it wasn't really optional in the conversation.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements and constraints of the version history system, then evaluate branching and rollback as potential features. Discuss how each would impact the data model, storage, and API design, and propose a design that balances flexibility with complexity.

Pro tip: Emphasize that branching and rollback are not just features but require careful consideration of data consistency and user workflows. Suggest starting with rollback as it's simpler and often more immediately valuable, then layering branching if needed.

1. Clarify Requirements

Ask questions to understand the use cases, expected scale, and consistency requirements for branching and rollback. This ensures your design addresses real needs.

2. Evaluate Impact on Data Model

Consider how branching would require a tree-like structure instead of a linear history, and how rollback might involve creating new versions or reverting pointers. Discuss trade-offs in storage and query complexity.

3. Assess API and User Experience

Outline how the API would change to support branch creation, switching, merging, and rollback operations. Consider how users would interact with these features and potential for errors.

4. Propose a Phased Approach

Recommend implementing rollback first as it's less complex and provides immediate value, then adding branching if needed. This shows pragmatic thinking and risk management.

5. Discuss Trade-offs and Alternatives

Summarize the trade-offs between simplicity and flexibility, and mention any alternative designs or mitigations for potential issues like merge conflicts or storage overhead.

Key Points to Mention

  • Data model changes: linear vs. tree-like version history
  • Storage and performance implications of branching (e.g., copy-on-write, deduplication)
  • API design for branch operations (create, switch, merge) and rollback
  • Consistency and concurrency control when multiple branches exist
  • User experience and potential for confusion with branching
  • Phased implementation: rollback first, then branching

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