Stripe·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

Stripe technical phone screen for a software engineer role. One question, pretty focused, basically just about building a lookup structure over a list of role assignment tuples and talking through the tradeoffs.

Questions Asked (1)

You have a list of (userId, accountId, role) tuples representing role assignments. Given a userId and accountId, return all roles that user holds on that account. Walk through your index choice and how you'd handle duplicate entries in the input.

Algorithms & Data StructuresTechnical Trade-offsData Modeling

Author's notes

I jumped straight to a hashmap keyed on (userId, accountId) and felt pretty good about it.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the expected operations and constraints (e.g., read-heavy vs. write-heavy, memory limits). Propose a hash map keyed by (userId, accountId) mapping to a set of roles, which gives O(1) lookup and automatic deduplication. Discuss trade-offs with alternative indexes like nested maps or sorted arrays, and explain how to handle duplicates by using a set or deduplicating during insertion.

Pro tip: Mention that using a set for roles not only handles duplicates but also makes role checks and updates efficient; if roles are fixed and small, a bitmask could be even faster. Also, consider whether the index should be built once or maintained incrementally, and how that affects concurrency and memory.

1. Clarify requirements and constraints

Ask about the expected operations (e.g., frequent lookups, updates, deletions), data size, memory limits, and whether the input is static or dynamic. This determines the appropriate index and data structures.

2. Propose a primary index

Suggest a hash map with a composite key (userId, accountId) mapping to a collection of roles. Explain that this provides O(1) average-time lookup and naturally groups roles per user-account pair.

3. Handle duplicates and choose role storage

Use a set to store roles to automatically deduplicate. If roles are a known small set, consider a bitmask or boolean array for memory efficiency. Discuss deduplication at insertion time vs. query time.

4. Discuss alternative indexes and trade-offs

Compare with nested maps (userId -> accountId -> roles) which may be more memory-efficient if many users have few accounts, or sorted arrays for range queries. Mention time/space trade-offs and when each might be preferable.

5. Address edge cases and scalability

Cover empty results, missing keys, concurrent updates, and memory overhead. Suggest sharding or partitioning if the dataset is large, and mention how to handle dynamic updates efficiently.

Key Points to Mention

Hash map with composite key (userId, accountId) for O(1) lookup
Using a set for roles to handle duplicates and enable fast membership checks
Trade-offs between nested maps and composite keys (memory vs. lookup simplicity)
Deduplication strategies: at insertion time vs. query time
Handling dynamic updates and concurrency (e.g., thread-safe structures or locks)
Memory considerations and potential optimizations like bitmasks for fixed role sets

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