Glassdoor Coding Interview Questions
26 Glassdoor coding interview problems with full optimal solutions — 17 easy, 7 medium, 2 hard. Every problem ships with multiple approaches (brute-force first, then the optimal), complexity tables for each, company-specific tips on what an Glassdoor interviewer values, and a FAQ section.
Showing 7 problems of 26
- #15mediumfoundational
15. Group Anagrams
Glassdoor's review-tagging pipeline buckets free-text snippets by shared character sets — this hash-map grouping problem is their go-to check for candidates who can think beyond brute enumeration when categorizing unstructured text at scale.
- #16mediumfoundational
16. Top K Frequent Elements
Surfacing the highest-rated companies out of millions of reviews is Glassdoor's bread and butter — this heap-based top-K problem tests whether you can rank by frequency without sorting everything first.
- #17mediumfoundational
17. Merge Intervals
Glassdoor's salary-range bands overlap across job titles and geographies — merging those intervals cleanly is a real backend task, which is why this sort-and-sweep problem shows up regularly in their coding screens.
- #18mediumfoundational
18. Longest Substring Without Repeating Characters
Extracting the longest unique-word run from a review snippet is analogous to what Glassdoor's NLP team does daily — this sliding-window problem tests whether you can maintain a dynamic window without backtracking on every character.
- #19mediumfoundational
19. Course Schedule
Glassdoor models skill prerequisites and career-path dependencies as directed graphs — cycle detection via topological sort is the pattern they reach for when verifying those graphs are actually traversable.
- #20mediumfoundational
20. Coin Change
Glassdoor's review-scoring system aggregates weighted signals — thinking about optimal sub-amounts before building the full aggregate maps directly onto this classic DP problem they use to filter for candidates who can construct bottom-up solutions.
- #21mediumfoundational
21. Product of Array Except Self
Glassdoor's salary-normalization pipeline needs per-element context built from all other values — this prefix-suffix product pattern is their benchmark for candidates who can think about array transformations without touching division.