Datadog Coding Interview Questions

Showing 13 problems of 100

• #1easyfrequently asked

  1. Two Sum

  Given an array of integers and a target, return indices of the two numbers that add up to the target. Datadog asks this as a warmup but pushes candidates to discuss how the same hashmap pattern scales to streaming pair-detection over high-cardinality metric IDs.

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• #2easyfrequently asked

  2. Valid Parentheses

  Given a string of brackets, determine if every opener has a matching closer in the correct order. Datadog frames this as a streaming log-parser warmup — the same stack discipline shows up when validating JSON log payloads on a high-throughput ingestion pipeline.

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• #3easyfrequently asked

  3. Merge Two Sorted Lists

  Merge two sorted linked lists into one sorted list. Datadog uses this as a stepping stone toward merging K sorted time-series streams — the underlying two-pointer pattern is identical to how their backend stitches ordered metric shards.

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• #6easyfrequently asked

  6. Search Insert Position

  Given a sorted array and a target, return the index where the target would be inserted. Datadog uses this as the bedrock for binary-search-on-time questions — every metric query that bisects timestamps uses this pattern.

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• #7easyfrequently asked

  7. Maximum Subarray

  Find the contiguous subarray with the largest sum. Datadog phrases this as 'find the peak metric burst' — Kadane's algorithm runs in a single pass and ports directly to a streaming aggregator over a metric window.

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• #9easyfrequently asked

  9. Merge Sorted Array

  Merge two sorted arrays in place, where the first has enough trailing space to hold both. Datadog uses this to test the reverse-iteration trick — the same backward-merge pattern they use when compacting two adjacent TSDB chunks without allocating a third buffer.

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• #17easyfrequently asked

  17. Best Time to Buy and Sell Stock

  Find the max profit from one buy and one sell. Datadog frames this as 'find the largest spike in a metric stream' — single pass, constant memory, identical to their min-tracking aggregator.

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• #19easyfrequently asked

  19. Single Number

  Every element appears twice except one. Find the singleton in O(n) time and O(1) space. Datadog asks this to test whether you know the XOR trick — a streaming-friendly aggregate that uses constant memory regardless of cardinality.

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• #20easyfrequently asked

  20. Linked List Cycle

  Detect whether a linked list contains a cycle. Datadog uses this as the Floyd-tortoise warmup before more complex cycle-detection problems in their dependency-graph traversals.

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• #21easyfrequently asked

  21. Min Stack

  Design a stack that supports push, pop, top, and getMin all in O(1). Datadog asks this because it's the same shape as a streaming min-aggregate that needs to handle rollbacks (transactional ingestion).

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• #23easyfrequently asked

  23. Majority Element

  Find the element that appears more than n/2 times. Datadog asks this because the Boyer-Moore vote algorithm is the canonical streaming-aggregate pattern for finding a heavy hitter in one pass with O(1) memory.

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• #29easyfrequently asked

  29. Reverse Linked List

  Reverse a singly linked list. Datadog uses this as the bedrock linked-list question — pointer manipulation here is required for harder problems like reverse-in-groups or merge-k-sorted.

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• #30easyfrequently asked

  30. Contains Duplicate

  Determine if any value appears at least twice in an array. Datadog uses this as the hashset warmup before count-distinct and HyperLogLog discussions for high-cardinality tag streams.

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