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Stripe·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jul 2026

Summary

Stripe coding screen for a software engineer role, basically one problem the whole time: parse a CSV of transactions, apply a fee ruleset, and output a clean result. Felt more like a real-world task than a leetcode grind, which was a nice change.

Questions Asked (1)

Q1

You are given a CSV describing payment transactions with fields like transaction ID, payment method, payment type, status, and amount. Apply a provided set of fee-calculation rules to each row and output the results as: id, transaction_type, payment_provider, fee.

Algorithms & Data StructuresAPI & IntegrationsTechnical Trade-offs
Author's notes

The parsing part felt fine at first, then the edge cases in the fee rules started stacking up and I realized I'd been skimming the spec instead of actually reading it.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the fee rules and edge cases, then outline a row-by-row processing pipeline that parses the CSV, applies the rules, and outputs the required fields. Emphasize modularity, error handling, and testability, and discuss trade-offs between simplicity and extensibility.

Pro tip: Mention that you would design the fee rules as a configurable strategy or rule engine so that new payment methods or fee structures can be added without modifying core logic. Also, highlight the importance of validating inputs and handling missing or malformed data gracefully.

1. Clarify requirements and rules

Ask questions to fully understand the fee-calculation rules, input CSV format, expected output, and any edge cases (e.g., refunds, currency, rounding).

2. Design the processing pipeline

Outline a modular approach: read CSV, parse each row, apply fee rules based on payment method/type, compute fee, and format output. Consider using a rule engine or strategy pattern for extensibility.

3. Handle edge cases and errors

Discuss how to handle missing fields, invalid amounts, unknown payment methods, and rounding. Propose logging and error reporting mechanisms.

4. Implement and test

Write clean, testable code with unit tests for each fee rule and integration tests for the full pipeline. Use sample data to verify correctness.

5. Discuss trade-offs and scalability

Talk about performance considerations for large files, potential for parallel processing, and trade-offs between a simple script and a more complex rule engine.

Key Points to Mention

  • Input validation and error handling for malformed CSV rows
  • Modular design with separation of concerns (parsing, rule application, output formatting)
  • Use of a rule engine or strategy pattern to encapsulate fee rules for maintainability
  • Handling of edge cases like refunds, zero amounts, and unknown payment methods
  • Testing strategy including unit tests for rules and integration tests for the pipeline
  • Performance considerations for large datasets (streaming, batch processing)

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