← Snowflake Interview Insights

Snowflake·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
May 2026Remote

Summary

Snowflake coding interview with a prefix-sum sliding window problem. Not the hardest thing I've seen but the constraint was a little tricky to get right under pressure.

Questions Asked (1)

Q1

Given an array and its prefix-sum array, find the length of the longest subarray (l, r) such that prefix[r] minus 2 times prefix[l] is at most k.

Algorithms & Data Structures
Author's notes

The two-pointer setup clicked for me pretty fast, iterate l and push r as far right as it'll go while the condition holds.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

First, restate the problem in your own words and clarify the definitions of the prefix array and the condition. Then, explain that the inequality can be transformed into prefix[r] - k <= 2*prefix[l], which suggests using a data structure to efficiently find the smallest l for each r. Finally, describe an O(n log n) or O(n) algorithm using a monotonic stack or binary search on a decreasing sequence of prefix values.

Pro tip: Mention that the prefix array is non-decreasing if the original array has non-negative numbers, but the algorithm should handle arbitrary integers. Also, emphasize that you would test edge cases like empty subarrays and large k.

1. Clarify the problem

Restate the problem and confirm the definition of the prefix array and the condition. Ask if the array can contain negative numbers and if the subarray must be non-empty.

2. Transform the inequality

Rewrite the condition prefix[r] - 2*prefix[l] <= k as prefix[r] - k <= 2*prefix[l]. This makes it easier to see that for each r, we need the smallest l such that 2*prefix[l] >= prefix[r] - k.

3. Choose an efficient algorithm

Propose using a monotonic stack to maintain indices with decreasing 2*prefix values, then for each r, binary search to find the smallest l satisfying the condition. Alternatively, use a two-pointer approach if the array is non-negative.

4. Analyze complexity

State that the monotonic stack + binary search approach runs in O(n log n) time and O(n) space. If the array is non-negative, a two-pointer approach can achieve O(n) time.

5. Test with examples

Walk through a small example to verify the algorithm, and discuss edge cases such as all elements negative, k very large, or no valid subarray.

Key Points to Mention

  • Transformation of the inequality to isolate l and r
  • Use of a monotonic stack to maintain candidate l indices
  • Binary search on the stack to find the optimal l for each r
  • Time and space complexity analysis
  • Handling of negative numbers and edge cases
  • Comparison with alternative approaches like two-pointer if applicable

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