Coinbase·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

May 2026Remote

Summary

Coinbase coding screen where they had me build a recipe management system from scratch, data model and all. Pretty straightforward if you know your hash maps, but designing the model yourself adds a wrinkle most people don't expect.

Questions Asked (1)

Design and implement a recipe management system supporting add, update, get, and delete operations. You define the data model yourself and should aim for O(1) time complexity where possible.

System DesignData ModelingAlgorithms & Data Structures

Author's notes

The CRUD part was fine, a hash map keyed by recipe id and you're basically done.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and defining a clear data model with Recipe and Ingredient entities. Then, design a storage layer using hash maps for O(1) operations, and discuss trade-offs for persistence and scalability. Finally, walk through the implementation of each CRUD operation, emphasizing time complexity.

Pro tip: Explicitly discuss how you would handle concurrent updates and ensure data consistency, as this is critical in financial systems like Coinbase. Also, mention idempotency for update and delete operations to avoid unintended side effects.

1. Clarify Requirements and Scope

Ask questions to understand expected scale, persistence needs, and any specific constraints. Define the core operations and non-functional requirements like latency and consistency.

2. Define Data Model

Design entities such as Recipe (with id, name, ingredients, steps) and Ingredient (with name, quantity, unit). Choose appropriate data types and relationships.

3. Design Storage and Indexing

Propose using an in-memory hash map (e.g., HashMap<RecipeId, Recipe>) for O(1) access. Discuss optional secondary indexes for queries by name or ingredient.

4. Implement CRUD Operations

Detail how each operation (add, update, get, delete) maps to hash map operations, ensuring O(1) average time. Handle edge cases like non-existent IDs.

5. Discuss Trade-offs and Extensions

Address persistence (e.g., write-through cache to a database), concurrency (locking or optimistic concurrency), and scalability (sharding). Mention how to maintain O(1) with distributed caches.

Key Points to Mention

Use of hash maps for O(1) average-case time complexity for CRUD operations.
Data model design with unique identifiers and normalized ingredients.
Handling of concurrent updates with locks or versioning to ensure consistency.
Idempotency of update and delete operations to prevent unintended side effects.
Trade-offs between in-memory storage and persistence for durability.
Potential need for secondary indexes to support queries beyond primary key.

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