Databricks coding interview
questions, leaked.
34 problems reported across recent Databricks interviews. Top patterns: array, hash table, string. The list below is what most reported candidates actually saw, plus the honest play if you can't grind all of it.
Databricks interviews are heavy on array and hash-table problems, with a median difficulty skew toward medium. Out of 34 reported questions, only one is easy. The interview will test your ability to manipulate arrays efficiently, design stateful systems (like counters and key-value stores), and handle binary search in unconventional contexts. You'll see design problems mixed in with algorithmic ones. If you hit a wall mid-assessment on something like Snapshot Array or Time Based Key-Value Store, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Top problems at Databricks
| # | Problem | Diff | Frequency | Pass % | Patterns |
|---|---|---|---|---|---|
| 01 | Design Hit Counter | MEDIUM | 100.0 | 69% | Array · Binary Search · Design |
| 02 | IP to CIDR | MEDIUM | 92.3 | 55% | String · Bit Manipulation |
| 03 | House Robber | MEDIUM | 87.4 | 52% | Array · Dynamic Programming |
| 04 | Design Tic-Tac-Toe | MEDIUM | 85.5 | 59% | Array · Hash Table · Design |
| 05 | House Robber II | MEDIUM | 84.8 | 44% | Array · Dynamic Programming |
| 06 | Time Based Key-Value Store | MEDIUM | 79.9 | 49% | Hash Table · String · Binary Search |
| 07 | Snapshot Array | MEDIUM | 71.9 | 37% | Array · Hash Table · Binary Search |
| 08 | Closest Leaf in a Binary Tree | MEDIUM | 67.0 | 47% | Tree · Depth-First Search · Breadth-First Search |
| 09 | Longest Palindrome by Concatenating Two Letter Words | MEDIUM | 67.0 | 54% | Array · Hash Table · String |
| 10 | Step-By-Step Directions From a Binary Tree Node to Another | MEDIUM | 60.3 | 56% | String · Tree · Depth-First Search |
| 11 | Smallest Range Covering Elements from K Lists | HARD | 60.3 | 70% | Array · Hash Table · Greedy |
| 12 | Minimum Absolute Difference Between Elements With Constraint | MEDIUM | 60.3 | 34% | Array · Binary Search · Ordered Set |
| 13 | Split Message Based on Limit | HARD | 57.5 | 43% | String · Binary Search · Enumeration |
| 14 | Web Crawler Multithreaded | MEDIUM | 54.1 | 50% | Depth-First Search · Breadth-First Search · Concurrency |
| 15 | Text Justification | HARD | 54.1 | 48% | Array · String · Simulation |
| 16 | Number of Flowers in Full Bloom | HARD | 54.1 | 57% | Array · Hash Table · Binary Search |
| 17 | Number of Recent Calls | EASY | 50.0 | 77% | Design · Queue · Data Stream |
| 18 | Count Integers in Intervals | HARD | 50.0 | 34% | Design · Segment Tree · Ordered Set |
| 19 | Longest Mountain in Array | MEDIUM | 44.6 | 41% | Array · Two Pointers · Dynamic Programming |
| 20 | Second Degree Follower | MEDIUM | 44.6 | 40% | Database |
| 21 | Merge Intervals | MEDIUM | 37.2 | 49% | Array · Sorting |
| 22 | Spiral Matrix | MEDIUM | 37.2 | 54% | Array · Matrix · Simulation |
| 23 | Find All Anagrams in a String | MEDIUM | 37.2 | 52% | Hash Table · String · Sliding Window |
| 24 | Finding Pairs With a Certain Sum | MEDIUM | 37.2 | 49% | Array · Hash Table · Design |
| 25 | Find the Length of the Longest Common Prefix | MEDIUM | 37.2 | 56% | Array · Hash Table · String |
| 26 | Longest Continuous Subarray With Absolute Diff Less Than or Equal to Limit | MEDIUM | 37.2 | 57% | Array · Queue · Sliding Window |
| 27 | Data Stream as Disjoint Intervals | HARD | 37.2 | 60% | Binary Search · Design · Ordered Set |
| 28 | Find Peak Element | MEDIUM | 37.2 | 47% | Array · Binary Search |
| 29 | First Missing Positive | HARD | 37.2 | 41% | Array · Hash Table |
| 30 | Maximum Profit in Job Scheduling | HARD | 37.2 | 54% | Array · Binary Search · Dynamic Programming |
| 31 | Course Schedule II | MEDIUM | 37.2 | 53% | Depth-First Search · Breadth-First Search · Graph |
| 32 | Design A Leaderboard | MEDIUM | 37.2 | 68% | Hash Table · Design · Sorting |
| 33 | String to Integer (atoi) | MEDIUM | 37.2 | 19% | String |
| 34 | Shortest Path in a Grid with Obstacles Elimination | HARD | 37.2 | 46% | Array · Breadth-First Search · Matrix |
Frequencies derived from public community-tagged interview reports. Click a row to view on LeetCode.
You have a week, maybe less. You can't out-grind the list above. StealthCoder runs invisibly during the actual Databricks OA. The proctor cannot see it. Screen share cannot detect it. Made by an Amazon engineer who watched the leaked-problem repo become an industry secret. He decided you should have it too.
Get StealthCoder- array20 · 59%
- hash table11 · 32%
- string9 · 26%
- binary search9 · 26%
- design9 · 26%
- sorting5 · 15%
- ordered set5 · 15%
- dynamic programming4 · 12%
- depth first search4 · 12%
- breadth first search4 · 12%
Arrays dominate the question pool at 20 problems, followed by hash tables at 11. String and binary-search problems appear frequently but rarely as standalone. The real pattern is compound: most medium problems fuse arrays with design or hash tables with binary search. Dynamic programming shows up in only 4 problems, so don't waste days on it. Depth-first and breadth-first search appear in exactly 4 problems each, mostly in tree contexts. The hard problems skew toward string manipulation and multi-constraint optimization. Drill array indexing, range queries, and hash-table value management first. Design problems expect you to reason about state and time complexity together. When you're live and facing a design problem you've never drilled, StealthCoder is your hedge, reading the requirements and handing you a scaffold in real time.
Companies with similar patterns
If you prepped for Databricks, these companies recycle ~60% of the same topics.
You've seen the list.
Now make sure you pass Databricks.
Memorizing every problem above in a week is a fantasy. StealthCoder is the hedge: an AI overlay that's invisible during screen share. It reads the problem on screen and surfaces a working solution in under 2 seconds. Made by an Amazon engineer who watched the leaked-problem repo become an industry secret. He decided you should have it too. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Databricks interview FAQ
How many array problems should I solve before the Databricks interview?+
Array problems make up 20 of 34 reported questions. Solve at least 12 to 15 before your OA, focusing on range queries, in-place modifications, and problems that combine arrays with hash tables or binary search. The rest you'll encounter live or catch with StealthCoder.
Is dynamic programming important for Databricks?+
No. Only 4 reported problems use DP, and they're not the centerpiece. House Robber and its variant appear, but they're secondary. Spend that study time on array-hash-table fusion and design patterns instead. DP is a filler topic here.
What design problems should I expect?+
Design Hit Counter, Design Tic-Tac-Toe, Time Based Key-Value Store, and Snapshot Array are the pattern. All involve stateful systems with queries over time or space. Study how to store, index, and retrieve data efficiently. Practice thinking about time and space tradeoffs in real time.
How much binary search do I need to know?+
Binary search appears in 9 reported problems but rarely standalone. You'll use it to find ranges, validate constraints, or optimize lookups within design problems. Don't drill binary search in isolation. Instead, solve problems like Snapshot Array and Time Based Key-Value Store, where binary search is a subcomponent.
What should I prioritize if I have one week left?+
One week means focus on array manipulation, hash-table value counting, and one design problem (Time Based Key-Value Store is a good anchor). Skip DP entirely. Skim string problems. You're not aiming for mastery, just pattern recognition so you don't blank mid-OA.