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Stripe·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Stripe technical phone screen for a software engineering role. Three-part coding problem that escalated pretty quickly from basic bookkeeping to something with actual edge cases worth thinking about.

Questions Asked (3)

Q1

You're given a list of transaction records as strings, each containing an account ID, timestamp, currency, and amount. Process all transactions and return the final non-zero balance for each (account, currency) pair.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

Part 1 felt easy and I maybe moved too fast.

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AI HintsAI Generated

Suggested Approach

Clarify the input format and edge cases, then propose a hash map keyed by (account, currency) to accumulate net balances. Discuss trade-offs between parsing on the fly versus pre-parsing, and how to handle floating-point precision and zero-balance filtering.

Pro tip: Mention that you would use integer arithmetic (e.g., cents) or a decimal library to avoid floating-point errors, and that you would filter out zero balances only after aggregation to avoid unnecessary removals.

1. Clarify requirements and assumptions

Ask about input format (delimiter, order of fields), data types (timestamp format, amount precision), and expected output (e.g., map or list). Confirm whether amounts can be negative and if zero balances should be excluded.

2. Choose data structures and parsing strategy

Decide on a hash map with a composite key (account, currency) and a numeric accumulator. Discuss whether to parse all records first or process in a streaming fashion, and how to handle large inputs.

3. Handle numeric precision and edge cases

Address floating-point issues by using integer cents or a decimal type. Consider edge cases like empty input, malformed records, duplicate timestamps, and currencies with different decimal places.

4. Implement and test the solution

Write pseudocode or actual code, then walk through a small example. Test with edge cases such as zero net balance, multiple currencies per account, and negative amounts.

5. Analyze complexity and trade-offs

State time and space complexity (O(n) time, O(k) space where k is number of unique pairs). Discuss trade-offs between simplicity and scalability, and potential optimizations like parallel processing.

Key Points to Mention

  • Use a hash map with a composite key (account, currency) for O(1) average-time updates.
  • Avoid floating-point errors by using integer arithmetic (e.g., cents) or a decimal library.
  • Filter out zero balances only after all transactions are processed.
  • Consider streaming vs. batch processing for large datasets.
  • Handle malformed or missing data gracefully (e.g., skip or raise errors based on requirements).
  • Discuss time and space complexity and potential optimizations.

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

Q2

Now process those same transactions in timestamp order and reject any debit that would push an account's balance for a given currency below zero. Rejected transactions have no effect. Return final non-zero balances.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

This is where I slowed down.

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AI HintsAI Generated

Suggested Approach

First, sort the transactions by timestamp, then iterate through them while maintaining a running balance per account and currency. For each debit, check if the balance would go negative; if so, skip it, otherwise apply it. Finally, filter out zero balances and return the result.

Pro tip: Clarify assumptions upfront: whether timestamps are unique, if credits can also be rejected, and the expected output format (e.g., map of account-currency to balance). This shows attention to detail and avoids rework.

1. Clarify requirements and edge cases

Ask about timestamp uniqueness, transaction types (debit/credit), currency handling, and output format. Confirm that rejected transactions are skipped entirely.

2. Sort transactions by timestamp

If not already sorted, sort the list of transactions in ascending order of timestamp. This ensures processing in chronological order.

3. Process transactions sequentially

Iterate through sorted transactions, maintaining a map of (account, currency) to balance. For each debit, check if balance - amount >= 0; if yes, apply, else reject.

4. Filter and return non-zero balances

After processing all transactions, remove any entries with zero balance and return the remaining balances in the required format.

Key Points to Mention

  • Time complexity: O(n log n) due to sorting, then O(n) processing.
  • Space complexity: O(m) where m is number of unique (account, currency) pairs.
  • Handling of multiple currencies per account: maintain separate balances.
  • Edge cases: negative amounts, zero amounts, duplicate timestamps (if allowed, process in any order? clarify).
  • Data structures: hash map for balances, sorting algorithm choice (e.g., stable sort if needed).
  • Correctness: invariant that balances never go negative after each step.

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

Q3

Extend the solution so that when a debit would overdraw an account, a designated platform account can cover the shortfall in the same currency. If the platform account also can't cover it, reject the whole transaction. Credits always go through. Return final non-zero balances for all accounts including the platform account.

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

This part took me the longest and I think I fumbled the edge case where the platform account itself is the one being debited.

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AI HintsAI Generated

Suggested Approach

First, clarify the requirements: debits that overdraw are covered by the platform account in the same currency, but if the platform cannot cover, the entire transaction is rejected; credits always succeed. Then, design a data model that tracks balances per account and currency, and implement a transaction processor that atomically updates balances, using the platform account as a fallback for debits. Finally, ensure the solution returns final non-zero balances for all accounts, including the platform account, and discuss trade-offs around atomicity, concurrency, and currency handling.

Pro tip: Emphasize atomicity and idempotency: in a real payment system like Stripe, transactions must be processed exactly once and balance updates must be atomic to avoid race conditions and double-spending. Mention using database transactions or locks, and consider how to handle concurrent transactions that might affect the platform account's ability to cover shortfalls.

1. Clarify Requirements and Edge Cases

Restate the problem to ensure understanding: debits that overdraw are covered by the platform account in the same currency; if platform can't cover, reject the whole transaction; credits always go through. Ask about concurrency, atomicity, and whether the platform account can go negative.

2. Design Data Model and Operations

Define data structures to store account balances per currency (e.g., a map of account ID to currency balances). Outline the transaction processing logic: for a debit, check if the account has sufficient funds; if not, check the platform account for the shortfall; if platform has enough, transfer the shortfall from platform to the account (or directly debit both), then debit the account; otherwise reject. For credits, simply add to the account balance.

3. Implement Transaction Processing with Atomicity

Describe how to implement the logic atomically, e.g., using database transactions or locks to prevent race conditions. Ensure that if any part fails (e.g., platform insufficient), no changes are made. Consider idempotency keys to handle retries.

4. Handle Concurrency and Consistency

Discuss strategies for concurrent transactions: locking order to avoid deadlocks, optimistic concurrency control, or serializable isolation. Explain how to ensure the platform account balance is checked and updated atomically with the account debit.

5. Return Final Balances and Discuss Trade-offs

After processing all transactions, return the final non-zero balances for all accounts, including the platform account. Discuss trade-offs: e.g., performance vs. consistency, whether to allow platform account to go negative, and how to handle multiple currencies.

Key Points to Mention

  • Atomicity: ensure that debiting the account and platform (if needed) happens as a single atomic operation to avoid partial updates.
  • Concurrency control: use locks or database transactions to prevent race conditions where multiple debits might overdraw the platform account.
  • Currency handling: the platform account must cover shortfall in the same currency; maintain separate balances per currency.
  • Rejection logic: if platform cannot cover, reject the entire transaction and leave balances unchanged.
  • Credits always succeed: no checks needed for credits, just add to balance.
  • Idempotency: consider idempotency keys to handle duplicate requests safely, especially in distributed systems.
  • Return non-zero balances: filter out accounts with zero balance in the final output, but include platform account if non-zero.

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