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Stripe·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say
Apr 2026Remote

Summary

Stripe coding screen, backend-flavored. The problem was a data validation pipeline and it had more moving parts than I expected for a single session.

Questions Asked (1)

Q1

Build a three-part key-value data validation routine: parse a record set, validate each record against a schema with required keys, types, and value constraints, then report all errors with the offending key and reason. The solution must handle nested keys and both missing and extra fields.

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

The parsing part was fine, I knocked that out fast.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and edge cases (e.g., nested keys, extra fields, error reporting format). Then outline a recursive validation function that traverses the schema and data, collecting errors with paths. Finally, discuss trade-offs like performance, error aggregation, and extensibility.

Pro tip: Mention that you'd separate parsing, validation, and reporting into distinct functions for testability and reusability, and consider using a schema definition format that supports nested structures (e.g., JSON Schema-like).

1. Clarify Requirements

Ask about the expected input format, schema definition, error reporting structure, and whether validation should stop at first error or collect all errors.

2. Design Data Structures

Define a schema representation that supports nested keys, required fields, types, and value constraints (e.g., min/max, regex). Plan an error object that includes the key path and reason.

3. Implement Recursive Validation

Write a function that traverses the schema and data recursively, checking for missing/extra keys, type mismatches, and constraint violations, accumulating errors.

4. Handle Edge Cases

Address nested keys, arrays, null/undefined values, and extra fields. Ensure error paths are clear (e.g., 'user.address.zip').

5. Discuss Trade-offs and Extensibility

Talk about performance (e.g., early exit vs. full error collection), schema evolution, and how to extend for custom validators.

Key Points to Mention

  • Recursive traversal for nested keys
  • Error aggregation with key paths and reasons
  • Handling missing and extra fields
  • Type checking and value constraints (e.g., min/max, regex)
  • Separation of concerns: parsing, validation, reporting
  • Trade-offs: performance vs. completeness, schema flexibility

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