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.
- #1easyfoundational
1. Two Sum
Given an array of integers and a target, return indices of the two numbers that add up to the target. N26 uses this as a warm-up to gauge hash-map fluency before deeper transaction-matching questions.
- #2easyfoundational
2. Valid Parentheses
Validate whether a string of brackets is balanced using a stack. N26 frames this as a sanity check before deeper questions about bracket-style transaction grouping.
- #3easyfoundational
3. Merge Two Sorted Lists
Merge two sorted linked lists into one sorted list. N26 uses this to probe pointer hygiene before scaling up to merging chronologically sorted multi-currency transaction streams.
- #4easyfoundational
4. Remove Duplicates from Sorted Array
Remove duplicates in-place from a sorted array and return the new length. N26 uses this for collapsing repeated transactions returned by upstream ledgers.
- #5easyfoundational
5. Remove Element
Remove all instances of a given value from an array in-place. N26 reframes this as filtering reversed transactions out of a daily settlement batch.
- #6easyfoundational
6. Search Insert Position
Find the index where a target would be inserted to keep a sorted array sorted. N26 uses this to confirm binary-search comfort before moving to time-ordered transaction lookups.
- #7easyfoundational
7. Plus One
Increment a number represented as a digit array. N26 uses this to surface carry-handling intuition, a precursor to integer-cents arithmetic for monetary amounts.
- #8easyfoundational
8. Merge Sorted Array
Merge two sorted arrays in-place into the first. N26 frames this as merging a new batch of cleared transactions into the running balance log.
- #9easyfoundational
9. Single Number
Given a non-empty array where every element appears twice except for one, find the single one. N26 uses this to test bitwise fluency before deeper ledger-reconciliation problems where one unmatched debit needs to be isolated.
- #10easyfoundational
10. Majority Element
Find the element that appears more than n/2 times in an array. N26 frames this as detecting the dominant currency in a multi-currency batch.
- #11easyfoundational
11. Happy Number
Determine if a number eventually reaches 1 when repeatedly replaced by the sum of squares of its digits. N26 uses it to gauge cycle-detection instinct before harder ACH retry-loop questions.
- #12easyfoundational
12. Isomorphic Strings
Decide whether two strings are isomorphic - characters in one map one-to-one to characters in the other. N26 uses this as a stand-in for column-mapping checks in their KYC field normalization pipeline.
- #13easyfoundational
13. Contains Duplicate
Return true if any value appears at least twice in the array. N26 uses this as the simplest version of their idempotency-key duplicate-detection check.
- #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.
- #23hardfoundational
23. Sliding Window Maximum
Given an array and a window size k, return the maximum in each window as it slides left to right. N26 uses this for real-time peak-debit detection in their fraud-monitoring stream.
- #24hardfoundational
24. Find Median from Data Stream
Design a structure that supports adding numbers and querying the median in better than O(n) per op. N26 ports this to streaming the rolling median transaction value per customer for outlier scoring.
- #25hardfoundational
25. LFU Cache
Design a cache that evicts the least frequently used key, breaking ties by recency, with O(1) get and put. N26 uses this for FX-rate caching, where high-volume corridors (EUR-USD) should stay hot while one-off corridors get evicted.