Blink Health·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

May 2026Remote

Summary

Blink Health software engineer round, basically one meaty coding problem the whole time. The problem looked straightforward at first glance but pagination and tie-breaking made it more annoying than expected. They also mentioned AI was fine for debugging but not for writing the solution, which felt like a reasonable constraint honestly.

Questions Asked (1)

Implement a function that fetches food outlets from a paginated HTTP API, filters by city and a minimum vote threshold, and returns the name of the highest-rated outlet. Tie-break by most votes when ratings are equal.

API & IntegrationsAlgorithms & Data Structures

Author's notes

The filtering logic itself was fine.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and edge cases, then outline a solution that handles pagination, filtering, and selection in a single pass to optimize performance. Discuss trade-offs between different approaches and emphasize clean, testable code.

Pro tip: Mention that you would handle pagination by following the 'next' link or incrementing page numbers until exhausted, and use a single pass to track the best outlet, avoiding storing all data. This shows awareness of memory efficiency and scalability.

1. Clarify requirements and constraints

Ask about API details: pagination method (page numbers, cursors), response format, rate limits, and error handling. Confirm filtering criteria: exact city match, vote threshold inclusive/exclusive, and tie-breaking rules.

2. Design the algorithm

Plan to fetch pages sequentially or in parallel (if allowed), filter outlets by city and votes, and track the highest-rated outlet with tie-breaking by votes. Use a single pass to minimize memory usage.

3. Implement with error handling

Write code that handles network errors, retries, and pagination termination. Ensure filtering and comparison logic is correct, including edge cases like no matching outlets.

4. Test and validate

Describe test cases: multiple pages, ties in rating, no outlets, API errors. Mention unit tests with mocked API responses to verify logic.

5. Discuss optimizations and trade-offs

Talk about time/space complexity, potential for parallel fetching, caching, and how to handle large datasets. Mention any assumptions made.

Key Points to Mention

Pagination handling: iterate through pages until no more data, using next page tokens or page numbers.
Filtering: apply city and vote threshold filters as early as possible to reduce data processed.
Selection logic: track max rating and tie-break by votes, updating only when a better outlet is found.
Error handling: deal with network failures, timeouts, and malformed responses gracefully.
Complexity analysis: O(n) time where n is total outlets, O(1) space for tracking best outlet.
Testing strategy: unit tests with mocked API responses covering edge cases.

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