Databricks Interview Process & Rounds
Databricks' process is a recruiter call, one technical phone screen, a virtual onsite of three to five rounds, and then a reference check and hiring committee review. In the few reports that list every step, the loop took about five to nine weeks from first contact to a final answer; onsite rejections can come the next day, while candidates who are asked for references wait one to three more weeks. The step that stands out in these reports is the one after the onsite: 12 posts come from candidates who were asked for references, and only 3 of them got an offer, several of the others after being told their interview feedback was strong.
Part of the full catalog of Databricks interview questions, covering every round.
AceOffer is not affiliated with, endorsed by, or sponsored by Databricks. Questions are reconstructed from interview experiences candidates shared, not from Databricks materials.
Key facts
- •5 distinct round types
- •34 questions reconstructed from 377 candidate reports
- •Reports span Jan 2025 – Aug 2026
- •Refreshed monthly · last updated October 2026
The Databricks loop, from candidate reports
Databricks' loop is a recruiter call, one technical phone screen, and a virtual onsite of two coding rounds, a system design round, and a behavioral or hiring-manager round. Staff-level loops can add a tech-fit project discussion, and one senior recruiter's list adds an architecture round. Then comes the part the reports talk about most: a hiring committee and reference checks after the onsite. Several candidates report strong-hire feedback on every round followed by a committee rejection with no technical reason given, and reference strength — including whether a current manager can be reached — is named as the deciding factor more than once. The coding rounds run 45-60 minutes, and implementation-style rather than LeetCode: firewall rules over CIDR blocks, a key-value store that reports its own QPS, a snapshot-set iterator, a multi-threaded log writer with synchronous disk writes. The pool is small enough that candidates report getting a question they had already prepared for, and the grading is strict about it: one candidate passed every phone-screen test case with a single small bug and was rejected the same day. Interviewers expect you to write your own tests. In system design the interviewer usually has a standard answer in mind and steers toward it; reports advise following that lead rather than arguing, and pseudocode is expected for the concurrency parts. Onsite results usually arrive within about a week; candidates who go on to references wait one to three weeks more, and a one-year re-apply freeze is reported.
Databricks interview timeline
| Step | Typical timing |
|---|---|
| Recruiter call to phone screen | 1-3 weeks |
| Phone screen to result | Same day to 2 days; occasionally a week |
| Phone screen pass to virtual onsite | 1-3 weeks |
| Onsite to rejection (no references asked) | Next day to 2 weeks |
| Onsite to reference request | 1-7 days |
| References to final decision | 1-3 weeks |
These ranges come from about 40 reports that give dates. One new grad who listed every step went from recruiter call to offer in under six weeks; two others took about seven and about nine weeks to a rejection, one of them including a redo round. Phone screen passes were reported the same day in 6 reports and the next day in 4. Onsite rejections without a reference step came the next day in 3 reports, and in 2 more the remaining onsite rounds were cancelled after a weak first day or round. Every report that went through references waited at least another week, and one candidate heard about three weeks after being told the onsite had passed.
The Databricks interview process, step by step
1. Recruiter call
A phone call; two reports give 30 minutes and two others say it was over in 5-10 minutes.
The recruiter covers your background, why Databricks, your timeline and competing offers, and walks through the loop. Experienced candidates in 3 reports were asked their current level, when they were last promoted, and how far they are from the next promotion, and two of them found it intrusive. New-grad and intern candidates in 3 reports were asked whether their internship gave a return offer, and one candidate who was pressed on this in an HR call was rejected two days later. One new grad describes this call as rarely the cut, though two experienced candidates were dropped right after it.
- →Have a plain answer ready for your level, promotion history and how long you have been at it; in two reports the committee's stated reason for a rejection was about tenure.
- →If you are a new grad or intern without a return offer, prepare a short, neutral explanation.
- →Ask the recruiter which rounds your loop will have; the names (Algorithm, Coding, System Programming, Architecture, Cross-Functional, Tech Fit) vary by level.
2. Technical phone screen
About 60 minutes of live coding in every report that gives a length; one problem with follow-ups.
Screens are mostly practical coding problems with a follow-up that changes the requirements, though a few reports describe a LeetCode-style question. The problems candidates report most are an optimal commute across transport modes, CIDR firewall rule matching, a key-value store that reports its recent QPS, and a snapshot set with iterators. The grading is strict: in 6 reports the candidate solved the problem and was still rejected (4 of them say their tests passed), pointing to a bug found along the way, a back-and-forth over the approach, or no time left for the follow-up. Some experienced candidates get a system design question as the screen instead (7 reports, all experienced hires), and 2 reports from 2026 describe a second phone screen being added.
- →Aim for bug-free code on the first run and leave time for the follow-up; in four reports the follow-up was never reached and each ended in rejection.
- →Write and run your own test cases without being asked. Two candidates' screens needed a mocked clock to test a time-based counter, so know how to fake time in your language.
- →Explain the code as you write it. One candidate whose tests all passed was told the explanation was too thin and had to take an extra screen.
- →If you are senior or staff, ask whether the screen is coding or design; reports show both.
3. Virtual onsite: Algorithm
60 minutes, live coding; one problem with a follow-up.
A more algorithmic round than Coding, though one candidate notes the two draw from a shared pool. Reported problems include the CIDR firewall, the QPS counter, a Fibonacci-tree path and the commute problem, and the follow-ups reported ask for a better complexity or a broader input. One new-grad candidate was told the round failed while the others were strong and was given a redo, which also failed on reaching the optimal complexity.
- →Expect the follow-up to need code, not just a description; one candidate was told the firewall follow-up had to be implemented.
- →Solve the first part quickly so the follow-up has time.
4. Virtual onsite: Coding
60 minutes (45-50 in one intern report) in CoderPad; implement a class against a set of requirements and run it.
This round is object-oriented implementation: a lazy array, tic-tac-toe on an m-by-n board, run-length and bit-packing encoders, a referral or revenue tracker. Several reports say the code has to run and you write your own tests in the editor, sometimes alongside cases the interviewer adds. One new-grad candidate was told code quality and maintainability mattered more than complexity, then concluded the optimal version was expected anyway. A long problem description is a known time sink: one candidate spent 20 minutes reading the encoder problem and did not finish.
- →Practise writing small test cases as you go and running them in the editor.
- →Clarify input order and edge cases before coding; on tic-tac-toe one candidate had to build tests around move order that the function did not specify.
- →Watch the clock on clarification. Several failed reports say the first 20 minutes went to understanding the problem.
5. Virtual onsite: System Programming (concurrency)
60 minutes; low-level design with code or pseudocode. Experienced-hire loops; not listed on the new-grad loops reported.
Recruiters call this System Programming or System Design Coding, and one recruiter told a candidate the loop has a specific concurrency round. Reported topics are a multi-threaded log writer with synchronous disk writes, a durable key-value store with a write-ahead log, a durable event writer, and a job scheduler. Two reports say the code does not need to run but the logic must be correct, and two more say pseudocode is acceptable. One candidate who had just taken the round advises against hiding behind thread-safe containers: show where you lock and unlock instead.
- →Be ready to explain the locking yourself; one candidate was questioned at length on how ConcurrentHashMap works inside.
- →Pin down the interviewer's preferences first. One candidate whose multi-threaded event logger round went well says the interviewer had a specific design in mind.
- →Ask early whether they want runnable code or pseudocode.
6. Virtual onsite: Architecture / System Design
60 minutes; typed in a document or a drawing tool. In one comparison, a senior loop had one more design round than an SDE II loop.
Reported prompts are the bookstore or book-seller platform, a strongly consistent distributed file system, Slack-style messaging with deletion, and payment or ad-budget systems. New-grad architecture rounds focus on APIs, database schema and request flow, with no diagram and the answer typed out (2 reports). Several candidates describe interviewers who probe every decision and seem to have a target answer in mind; one staff candidate who failed a file system design screen says they talked from intuition alone. Reports name Google Docs, CoderPad's drawing mode and a platform with a built-in whiteboard as the tools.
- →Write out APIs and schema concretely; one new grad was asked for each request's payload.
- →Raise failure modes and idempotency yourself; bookstore reports center on what happens when a downstream call or a hold fails.
- →Explain the reason for each decision out loud and follow the interviewer's direction rather than defending your first design.
7. Virtual onsite: Cross-Functional / hiring manager
30-45 minutes with a manager; behavioral questions and a project deep dive.
Questions are standard: conflict, ambiguity, ownership, critical feedback, your hardest project, why Databricks. This round can decide the loop on its own: one candidate had strong-hire feedback on three technical rounds and lost the offer because the manager was very negative, and another heard nothing back after a manager round that turned condescending. One candidate who was assessed at senior staff level suspects their examples were too small in scope for it.
- →Prepare a project you can defend in detail under interruption; one new grad was asked about the architecture of the team they interned on.
- →Pick examples that match the level you are interviewing for.
8. Tech Fit / project deep dive (L6 and staff)
With a senior engineer or org tech lead; length not reported.
One L6 candidate lists a Tech Fit round with an org tech lead, alongside only one coding round, and one staff candidate had a project deep dive where the interviewer interrupted from the first minute. One ML candidate was scheduled for an ML tech-fit round.
- →Lead with the hardest technical decision in your project; one staff candidate ran out of time because the answers were at the end of the story.
9. Extra round (sometimes)
One or two added interviews after the onsite, usually design.
Six reports describe an added round after the onsite, most often a second system design when one design round went poorly. Two of those candidates received offers; the others were rejected, including one staff candidate who sat seven rounds in total. One commenter who was rejected was told the add-on went well but the original round still counted against them.
- →Treat an added round as a second chance on the weak area; prepare that area again rather than repeating what went well.
How the Databricks loop differs by role
New grad
Usually four onsite rounds: Algorithm, Coding, Architecture and Cross-Functional, sometimes split over two days (one new grad had only three). None of the three new-grad loops that list their rounds has a system programming round, and new-grad architecture rounds stay at API and schema level. One European new grad in Amsterdam felt the bar was slightly lower than in North America.
Intern
A recruiter call, with no technical phone screen in several intern reports, then two technical rounds (algorithms and object-oriented coding; 45-50 minutes each in CoderPad in one report), then a behavioral round with an engineering manager. Feedback goes to the committee after the manager round; one intern waited three weeks after it, and a commenter who had passed both technical rounds was rejected there.
Experienced SWE (SDE II / L4)
Four rounds in two reports that list them: two coding rounds, one system programming round and a behavioral round. One candidate notes that below senior the design slot is usually the concurrency round in pseudocode, and an SDE II commenter says their loop had no architecture round.
Senior (L5)
Five rounds: Cross-Functional, Algorithm, System Design Coding, Coding, and Architecture and Design, as one recruiter listed it. Some senior screens are a system design question instead of coding. Level can move: one recruiter said performance would decide between senior and staff, and one candidate applying for L5 was refused an L5 offer by the committee over time spent at that level.
Staff / L6
One L6 loop was system design, one coding round, system programming, a manager round and a Tech Fit project review. One staff candidate who reached a hiring manager directly skipped the phone screen and went straight to five onsite rounds, then two more.
Machine learning engineer
Five MLE reports describe a regular coding round plus ML rounds: an ML design round (harmful content detection appears in four of them), ML and LLM fundamentals asked verbally, and on some loops an ML coding round such as implementing gradient descent. One candidate recruited for senior MLE was rejected at senior staff level, and another says the ML round did not match the job description.
Full-stack and frontend
In one 2026 thread, several full-stack candidates say the recruiter asked them to choose a frontend or backend focus. One senior full-stack loop had five rounds: frontend system coding, frontend coding, backend system design, algorithm and behavioral. Frontend design rounds focus on data modeling and API design rather than scale. One backend candidate was asked a UI question first and switched to object-oriented design after declining.
After the final round
After the onsite, the recruiter collects feedback and, if it is positive, asks for references; reports give three to five, usually including a current or former manager. In 12 posts the candidate reached the reference step: 3 got offers, 8 were rejected, most with no feedback, and one was told feedback was positive but was not offered the level they applied for. Reasons recruiters gave include references not strong enough and no manager among them (one candidate had never changed jobs), a past short tenure, and too long at one level, and one recruiter said the rejection was not technical. Four candidates believe Databricks also contacted people they did not list, from their current company or LinkedIn network, while one recruiter said they only reach out to confirmed references. Commenters say the hiring committee then reviews all interview feedback together with your resume. Two reports describe team matching between the phone screen and the onsite, and one commenter's process was paused because no local team matched. Two reports cite a one-year cooldown before you can reapply.
What does Databricks ask in each round?
Databricks interviews span 5distinct round types, shown below. Counts reflect distinct questions per round across the loops we’ve indexed.
- •Clarifying requirements exhaustively before writing a line. On the log writer the interviewer had a specific implementation in mind, and the report that passed says the round turned on pinning down preferences upfront; another advises recognising early when the interviewer has a direction and aligning with it.
- •Writing your own test cases and running them before the interviewer asks. Two debriefs cite test coverage directly — one rejection read ‘test cases not comprehensive’ — and a tic-tac-toe candidate lost time because the function never specified move order and the tests had to establish it.
- •Showing the concurrency primitives rather than hiding behind a thread-safe container. One candidate who had just taken the round advised against thread-safe data structures: demonstrate when to lock and unlock. The Slack design round asks the same thing in reverse — ‘why not a plain HashMap, and how does ConcurrentHashMap work inside?’
- •Raising the failure mode before the interviewer does. The bookstore round's recorded pass is the candidate who volunteered that the cheapest copy might be sold between the quote and the hold, and that the downstream sellers must not be overloaded; the KV-cache round rewards addressing WAL truncation and snapshot coordination unprompted.
- •Following the interviewer's lead in design. Reports describe interviewers who guide toward the answer they want and probe every decision; the advice is to listen and adapt rather than defend, and to explain each choice out loud because nothing is assumed understood.
- •Shipping code with a bug. One candidate passed all test cases with one small bug and received a same-day rejection; another wrote a working solution slowly with bugs and got no follow-up questions, which the report reads as the interviewer having already decided.
- •Running out of time on the second problem or the optimal version. A redo round failed on not reaching the O(n) solution with code incomplete; a bit-manipulation second problem sank another loop; and on the commute problem the interviewer rejected a min-heap solution and one BFS per transport mode, insisting on a single pass.
- •Using a thread-safe structure you cannot explain. Reaching for ConcurrentHashMap without knowing its internals is a recorded failure in the multi-threaded Slack variant, and the log writer is graded on whether busy-waiting was actually eliminated.
- •Walking into the distributed file system round on intuition. One rejection says it plainly — ‘talked entirely from gut feeling, so I failed’ — and the file system round explicitly rejects S3-style last-writer-wins copied from a textbook when the requirement is strong consistency.
- •Treating the behavioral and hiring-manager rounds as a formality. One loop had strong hire on all three technical rounds and failed on a very negative HM round; staff candidates were dinged for examples whose scope was too small for the level.
How to prepare for the Databricks interview
1. Prepare your references before the onsite
Only 3 of the 12 candidates in these reports who reached the reference stage got offers, and several were rejected after strong interview feedback. Line up three to five people now, including a current or former manager, and tell them what you worked on together.
2. Drill the practical coding problems to bug-free
Work through the commute, CIDR firewall, QPS counter, snapshot set, lazy array, tic-tac-toe and encoder problems until you can write each cleanly on the first run with your own tests. Six candidates were rejected at the screen after solving the problem, four of them with their tests passing.
3. Practise concurrency by hand
For experienced loops, implement a multi-threaded log writer and a write-ahead-log key-value store with explicit locks and condition variables, and be able to explain what a thread-safe map does internally.
4. Rehearse design at the API and schema level
Practise the bookstore, distributed file system and Slack prompts by writing out APIs, schema and failure handling, since several rounds are typed rather than drawn. Know storage internals well enough to answer follow-ups without guessing.
5. Prepare the manager round as seriously as the code
Have project stories at the right scope for your level, a reason for wanting Databricks, and calm answers on tenure and promotions; in one report a single negative manager round ended a loop with strong technical feedback.
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