Databricks’ Interview Process & Questions

Databricks' Interview Process & Questions

The info below is based on conversations with Databricks engineers

Last updated: October 14, 2026

Databricks' Interview Process for Software Engineers: 4 Steps

Mid to senior-level engineers interviewing at Databricks can expect the following process:

Databricks has a hybrid hiring process. Candidates are typically matched to a specific part of the organization early on, and you'll interview for a specific role, but your interviewers will not necessarily be from your future team. There is also scope to switch roles after the onsite. According to our sources, about a quarter of candidates pivot to another team after completing their onsite interviews.

The entire process can take up to 8 weeks, making it one of the longer hiring processes in the industry. Recruiters are upfront about this timeline with candidates.

General tips:

Step 1: Recruiter Call

Databricks' recruiter screen lasts about 30 minutes, and it’s pretty standard fare. They'll ask about your previous experience, your interest in Databricks, and go over the specific role you're applying for. At this stage, your profile (resume, referral information, location preferences) begins to be shared with engineering leads for potential team matching.

It’s important to not reveal your salary expectations or where you are in the process with other companies. We’ve written a detailed post about salary negotiation that lays out exactly what to say if recruiters pressure you to name the first number.

Step 2: Technical Phone Screen

The technical phone screen lasts about 1 hour with an engineer. You'll use CoderPad or a similar online IDE with runnable code. Expect LeetCode-style questions, typically medium to hard difficulty. One engineer we spoke with, who had just gone through the process, told us:

The question was one of the LeetCode questions for Databricks. I was able to find it by searching for the common Databricks questions from the past 3 months.

Questions candidates have faced include a weighted paths problem (graph optimization), the house robber problem, and the LRU cache problem, all of which build in difficulty as time permits.

Step 3: Hiring Manager Call

The timing of the hiring manager call varies. Some candidates have it before the onsite as described here, while others don't meet the hiring manager until after. Confirm the order with your recruiter early on. At staff level, candidates report the hiring manager being heavily involved throughout the process, including post-onsite. One staff-level candidate had the hiring manager directly provide offer numbers rather than going through the recruiter, which is unusual. If you're interviewing at that level, don't be surprised if your HM is a more active presence than you'd expect.

This interview is primarily behavioral, covering your background and experience, what you've worked on and enjoy working on, and questions you have about Databricks and the specific organization. If a hiring manager is unavailable, you might be interviewed by the Director of Engineering for the organization in question.

Step 4: Onsite Interviews

At this point, candidates interview for specific teams based on their background and interests. Onsite interview loops vary slightly depending on role (ML, frontend, backend, etc.) and seniority level, but the below is generally what you'll get:

Types of Interview Questions to Expect at Databricks

Databricks' technical questions tend to lean toward the difficult side. For coding interviews, expect LeetCode hard more than medium questions.

Coding

There are usually 3 coding rounds. Two will focus on Data Structures and Algorithms, and one focuses on concurrency and multithreading. The coding rounds that include algorithm questions are LeetCode medium or hard in terms of level.

Coding 1: Algorithms

This round tends to be more implementation-focused than algorithmically complex. One example we heard involved IAP to CIDR (checking if IP address ranges fit into CIDR notation). Another was a variable-sized tic-tac-toe game implementation question. One candidate described a bit compression and decompression problem: given blocks of bits, compress runs using a specific algorithm (a sequence like 0 1 1 1 1 1 1 0 compresses to 0 1-6 0), then decompresses back to the original. The algorithm itself isn't hard, but the problem is full of subtle edge cases that can send you into rabbit holes quickly. The challenge is writing clean, correct code rather than finding an elegant solution. Budget time for edge cases.

Coding 2: Algorithms

This round is closer to standard LeetCode, introduced progressively. One candidate described it as a dressed-up LeetCode question: a simple version first, then layers added until it built to something slightly more complex than what you'd find on LeetCode directly. The moving average from a data stream is a representative example of the domain. You receive numbers one at a time and need to return values like max, min, and average on demand, with some added complexity around space. The underlying pattern is standard LeetCode. Don't over-prepare expecting something exotic.

Candidates report both algorithm rounds tend to involve tricky optimizations. You can use a brute force solution to make progress, but you should be thinking of optimizations throughout.

Coding 3: Concurrency/Multithreading

In the Concurrency and Multithreading coding round, you might be asked to implement an efficient logger that processes messages in a queue. This round is considered particularly challenging by most candidates, and one of the more unusual rounds you'll encounter anywhere. It is open-ended and low-level, conducted in pseudocode rather than a specific language. One staff-level candidate was asked to optimize a system for writing logs to disk. The problem sits somewhere between LeetCode, system design, and hardware trivia: you need to know your concurrency primitives and how to apply them, understand tradeoffs and ask good questions about the problem space (what are the durability requirements? How bursty are the writes?), and have some grounding in hardware performance. The interviewer noted that the candidate was expected to have a sense of how long an SSD write operation takes, for example. The interviewer will keep shifting the problem as you go, adding conditions and asking you to propose new solutions. There is no clear win criteria. That said, one candidate who worked through LeetCode's entire concurrency section beforehand found that just being comfortable with the structures was very helpful, even though the round itself goes well beyond standard LeetCode. The degree of open-endedness may scale with seniority. One engineer we spoke to, who is familiar with the process, told us:

This question wasn’t on LeetCode, but preparing by solving the LeetCode questions on concurrency and multithreading will be a huge help.

Below are the technical topics you’re likely to encounter in Databricks interviews. To compile this list, we did two things. First, we spoke to some current and former Databricks engineers. Then we cross-referenced all the anecdotes we heard with Glassdoor data AND our own dataset of mock interviews:

Hash Maps

[Questions
& tips](/content/hash-tables-interview-questions/index.html)

[Watch 4

interview replays](/content/mocks?technical=hash-maps/index.html)

Binary Search

[Questions
& tips](/content/binary-search-interview-questions/index.html)

[Watch 7

interview replays](/content/mocks?technical=binary-search/index.html)

Arrays

[Questions
& tips](/content/arrays-interview-questions/index.html)

[Watch 21

interview replays](/content/mocks?technical=arrays/index.html)

Strings

[Questions
& tips](/content/strings-interview-questions/index.html)

[Watch 14

interview replays](/content/mocks?technical=strings/index.html)

Graphs

[Questions
& tips](/content/graphs-interview-questions/index.html)

[Watch 10

interview replays](/content/mocks?technical=graphs/index.html)

Sorting

[Questions
& tips](/content/sorting-interview-questions/index.html)

[Watch 12

interview replays](/content/mocks?technical=sorting/index.html)

System Design

Their system design questions are pretty standard, but they will expand on the initial question to dig deeper into your depth of knowledge. One example we heard involved designing a service that provides customers with the cheapest copy of a book they're searching for, which requires considering integration with different book distributors, search functionality, and purchase flows.

Be prepared to use Google Docs for these interviews rather than whiteboarding tools, which some candidates found unusual. This choice seems to be up to the individual interviewer, so don’t be caught off guard!

Check out our guide to system design interviews to help you prepare.

Cross-Functional/Behavioral

This interview is with the hiring manager and includes standard behavioral questions about your past experiences and projects. The recruiter may brief you on the hiring manager's style beforehand. You’ll be asked about your past projects and explore areas of conflict resolution and teamwork. Expect questions like "Tell me about a time you had a conflict with a coworker" and "Describe a project you're most proud of," with deep follow-up questions on specifics.

How Databricks Makes Hiring Decisions

After the onsite interviews, Databricks has a thorough evaluation process that consists of multiple layers of review.

Reference checks are an important part of the evaluation, typically involving 1 manager and 2 more senior team members. Databricks weighs references heavily, and the process can be lengthy. One candidate went through multiple rounds of reference gathering after being told initial references were not recent or detailed enough. Line up strong, specific references early and make sure they can speak to recent, concrete work.

Next comes the Hiring Committee review. Unlike the interview panel, this is a separate committee that reviews all aspects of your candidacy: interview feedback, background, career trajectory, and references. Our sources emphasize that the final decision is holistic, so having every aspect of your application as strong as possible is crucial.

Finally, the VP of Engineering reviews the complete candidate packet and has the final say on hiring decisions. One of our sources reported failing at this step despite positive feedback in earlier rounds, suggesting that the bar remains high throughout the entire process.

In some cases, candidates might be asked to complete an additional take-home assessment after the onsite. While this is rare, it might be used when the recruiter believes it could strengthen a candidate's application. These assessments can take around 5 hours to complete and may involve specialized problems such as database challenges.