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Affirm·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Apr 2026

Summary

Interviewed for a software engineering role at Affirm and got a transaction processing problem that felt deceptively simple at first glance. The follow-ups are where it gets real.

Questions Asked (1)

Q1

Given a list of transactions for a single day where each entry has a timestamp, user ID, and amount (positive for credits, negative for debits), compute the end-of-day balance for every user and return a map of user ID to net balance.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

Pretty much a hash-map accumulation problem.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., input size, memory limits, whether the list is sorted) and then propose a single-pass hash map solution that accumulates net balances per user. Discuss time and space complexity, and consider edge cases like empty input or large datasets.

Pro tip: Mention that you would use a hash map for O(1) average-time updates, but if the dataset is huge and memory is constrained, you could sort by user ID and process in batches. This shows you think about scalability and trade-offs.

1. Clarify requirements and constraints

Ask about input size, memory limits, whether transactions are sorted, and if the output should include users with zero net balance. This ensures you design the right solution.

2. Choose data structure and algorithm

Propose using a hash map (dictionary) to accumulate net balances per user in a single pass. Explain that this gives O(n) time and O(u) space, where u is the number of unique users.

3. Walk through an example

Trace the algorithm on a small sample input to demonstrate correctness and show how credits and debits are handled.

4. Analyze complexity and trade-offs

Discuss time and space complexity, and mention alternative approaches (e.g., sorting) and when they might be preferable, such as when memory is limited.

5. Handle edge cases and finalize

Address edge cases like empty input, users with zero net balance, and potential integer overflow. Summarize the solution and confirm it meets requirements.

Key Points to Mention

  • Use a hash map to accumulate net balances per user in a single pass.
  • Time complexity: O(n) where n is the number of transactions; space complexity: O(u) where u is the number of unique users.
  • Consider whether to include users with zero net balance in the output.
  • Discuss trade-offs: hash map vs. sorting approach for memory-constrained environments.
  • Handle edge cases: empty transaction list, large amounts causing overflow, and duplicate user IDs.
  • Mention that the solution is scalable and can be adapted for streaming data if needed.

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