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Stripe·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Stripe coding screen for a software engineer role. One problem, clean setup, and the question was more about knowing your data structures than anything clever.

Questions Asked (1)

Q1

Given a list of transactions with account name, timestamp, currency, and amount columns, return only the accounts whose total balance is non-zero, along with their final balance.

Algorithms & Data StructuresData Modeling
Author's notes

Jumped straight to a hash map keyed by account name and summed the amounts.

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AI HintsAI Generated

Suggested Approach

Clarify the data model and edge cases (e.g., multiple currencies, timestamps) before coding. Then, outline an algorithm that aggregates balances per account and filters out zero balances, discussing efficiency and correctness.

Pro tip: Mention that in a real system like Stripe, you'd likely need to handle currency conversion or maintain separate balances per currency, and discuss how to scale the solution for large datasets.

1. Clarify Requirements

Ask about data types, whether amounts can be negative, how to handle multiple currencies, and if timestamps affect the final balance (e.g., only latest per account).

2. Design Data Model

Decide on a data structure to store balances per account, such as a hash map, and consider if you need to track balances per currency separately.

3. Process Transactions

Iterate through the list, updating the balance for each account. If multiple currencies are involved, either convert to a common currency or maintain separate balances.

4. Filter and Output

After processing, filter out accounts with zero total balance and return the remaining accounts with their final balances.

5. Analyze Complexity

Discuss time and space complexity (O(n) time, O(m) space where m is number of accounts) and potential optimizations for large-scale data.

Key Points to Mention

  • Handling multiple currencies: either convert to a base currency or maintain separate balances per currency.
  • Edge cases: accounts with zero balance after aggregation, negative balances, and transactions with timestamps out of order.
  • Data structures: using a hash map for O(1) average-time updates and lookups.
  • Scalability: considerations for large datasets, such as streaming processing or distributed aggregation.
  • Correctness: ensuring that all transactions are accounted for and that the final balance is accurate.
  • Output format: returning only non-zero accounts with their final balance, possibly as a list of tuples or a map.

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