N26 Coding Interview Questions
25 N26 coding interview problems with full optimal solutions — 13 easy, 9 medium, 3 hard. Every problem ships with multiple approaches (brute-force first, then the optimal), complexity tables for each, company-specific tips on what an N26 interviewer values, and a FAQ section.
Showing 9 problems of 25
- #14mediumfoundational
14. LRU Cache
Design a data structure that supports get and put in O(1) time and evicts the least recently used key when capacity is exceeded. N26 asks this because their account-balance hot cache must evict cold customers without scanning.
- #15mediumfoundational
15. Number of Islands
Count connected components of 1s in a 2D grid. N26 uses this as a stand-in for clustering related transactions during fraud-graph triage.
- #16mediumfoundational
16. Course Schedule
Decide whether you can finish all courses given prerequisite pairs - really a cycle-detection question on a directed graph. N26 ports this to detecting circular dependencies in KYC verification step graphs.
- #17mediumfoundational
17. Implement Trie (Prefix Tree)
Implement a trie supporting insert, search, and startsWith. N26 maps this onto IBAN-prefix routing: every European IBAN starts with a country code plus a check digit, and a trie answers prefix lookups in O(len).
- #18mediumfoundational
18. Kth Largest Element in an Array
Return the kth largest element in an unsorted array. N26 frames this as picking the kth biggest transaction in a daily settlement batch for variance reporting.
- #19mediumfoundational
19. Product of Array Except Self
Return an array where each element is the product of every other element, without division and in O(n). N26 uses it to test prefix/suffix discipline before harder running-balance ledger questions.
- #20mediumfoundational
20. Search a 2D Matrix II
Search a value in a 2D matrix sorted both row-wise and column-wise. N26 uses this as a model for indexed lookups in their FX-rate-by-day pivot tables.
- #21mediumfoundational
21. Top K Frequent Elements
Given an integer array, return the k most frequent elements. N26 frames it as picking the top-k merchant categories per customer for category-spend insights.
- #22mediumfoundational
22. Subarray Sum Equals K
Count the number of contiguous subarrays whose sum equals k. N26 asks this because their AML rules flag any contiguous window of transactions summing to a structuring threshold.