Databricks Interview Questions and Answers (2026)

The Databricks interview process for software engineers is a recruiter call, a 60-minute live coding screen, and a virtual onsite of about four interviews: an algorithms round, a practical coding or API round, a systems or system design round, and a behavioral round scored against Databricks’ six culture principles. Reference checks come before the offer. Coding questions are LeetCode medium in style but often framed as small designs, such as a hit counter, tic-tac-toe or IP-to-CIDR conversion, and interviewers ask you to write your own tests.

Databricks’ own interview prep page says the full process usually takes two to three months and that feedback is targeted within 48 hours of the final interview. Self-reported pass rates on Taro are low: 12% across 97 US software engineer reports.

Databricks interview process

Recruiter screen~20-30 min
Technical screen60 min
Onsite: algorithms (DSA)~60 min
Onsite: coding or API~60 min
Onsite: systems or system design~60 min
Onsite: behavioral~45-60 min
Reference checks-

Round	Duration	What it tests
Recruiter screen	~20-30 min	Background, internship or past work, location, timeline
Technical screen	60 min	One LeetCode-style problem, implemented and tested live
Onsite: algorithms (DSA)	~60 min	A medium problem with follow-ups; a 2025 hire had a bit manipulation question
Onsite: coding or API	~60 min	Implementation-heavy task, such as building an API for a practical problem
Onsite: systems or system design	~60 min	Concurrency, data handling and scaling; one 2025 hire stressed it was “systems”, not classic system design
Onsite: behavioral	~45-60 min	Hiring manager round on past projects and Databricks’ culture principles
Reference checks	-	Listed by Databricks as step 6 of 7 before the decision and offer

Durations for onsite rounds are not published by Databricks; the hour-long length comes from candidate reports of the screen.

Databricks interview questions with answers

Q: Design a hit counter that returns the number of hits in the past five minutes.

Keep a fixed array of 300 buckets indexed by timestamp mod 300, each holding the timestamp it was last written and a count. On hit(t), if the bucket’s stored timestamp is not t, reset it to t with count 1, otherwise increment. getHits(t) sums buckets whose stored timestamp is within the last 300 seconds. That is O(1) per hit and O(300) per query with constant memory, which beats a queue of raw timestamps when traffic is bursty. Follow-ups to expect: make it thread-safe (a lock per bucket or atomic counters) and support a configurable window.

Q: Convert an IP range into the smallest list of CIDR blocks (IP to CIDR).

Convert the start IP to a 32-bit integer. While addresses remain, the largest block you can emit starting at x is limited by the lowest set bit of x (x AND -x) and by the number of addresses left. Shrink that block size by halves until it fits, emit x/prefix where prefix is 32 minus log2(size), then advance x by size and subtract size from the remaining count. Edge cases interviewers check: x equal to 0, where the lowest set bit trick needs special handling, and ranges that end exactly on a block boundary.

Q: Write a multithreaded web crawler that stays on one hostname.

Use a thread-safe visited set and a work queue. Workers take a URL, fetch its links through the provided HtmlParser, keep only links with the same hostname, and add unseen ones to the set and queue in one atomic step so two workers cannot enqueue the same URL. Stop when the queue is empty and no worker is busy, which needs an in-flight counter, not just an empty-queue check. In Java an ExecutorService with ConcurrentHashMap.newKeySet() works; in Python use ThreadPoolExecutor and a lock around the check-and-add.

Q: Design tic-tac-toe on an n by n board with O(1) moves.

Do not scan the board. Keep a counter per row, per column, and one each for the two diagonals. Player one adds 1, player two adds -1. After a move at (r, c), update rows[r], cols[c], the diagonal if r equals c, and the anti-diagonal if r plus c equals n minus 1. If the absolute value of any updated counter reaches n, that player wins. Memory is O(n) and each move is O(1). Mention input validation, since interviewers ask what happens on an occupied square.

Q: How would you design a key-value store that supports snapshots or versioned reads?

Store each key as a list of (version, value) pairs sorted by version, and keep a global version counter that a snapshot captures. A read at snapshot s binary-searches the key’s list for the largest version not greater than s. Writes append with the next version, so they never block readers. Old versions can be garbage collected once no live snapshot references them. This shape is useful in Databricks systems rounds because Delta Lake’s time travel works on the same idea at table level.

Databricks hiring process, step by step

Databricks publishes a seven-step hiring process on its careers site: identify an opening, apply online, connect with talent acquisition, skill assessments, interviews, reference checks, then decision and offer. For interviews it describes a recruiter call, a pre-onsite screen that may be a hiring manager screen, technical assessment or skill evaluation, and an onsite loop of usually four to six interviews. Some go-to-market and executive roles add a presentation.

A few rules from the same page matter for engineers:

Interviews are on Google Meet unless your recruiter says otherwise. Test your camera and screen sharing first.
Dress is business casual.
Do not bring confidential code or documents from a current employer, and do not use your work laptop for any Databricks exercise.
University postings say Databricks can only consider one application in 30 days, so apply for the single location you want most.

Databricks new grad and intern interview

Databricks’ Software Engineer - New Grad (2027 Start) posting covers Bellevue, Mountain View, San Francisco and Vancouver and asks for a fall 2026 or spring 2027 graduation in computer science, engineering or a related field. It wants implementation skill in a language such as Python, Java or C++, plus knowledge of algorithms, data structures and object-oriented design. Teams range from backend and infrastructure to databases, systems and customer-facing products. A separate Distributed Data Systems new grad posting is open for Bellevue and Mountain View.

Reported new grad loops from 2025:

A Bellevue new grad (September 2025) had a 20-minute recruiter call that walked through a previous internship and how it ended, then a 60-minute technical interview with an engineer.
A San Francisco new grad (October 2025) reached a final round of four interviews, including system design and a task to construct an API for a practical problem, and did not get an offer.
A US software engineer who got an offer in October 2025 had one LeetCode-style screen, then an onsite of a LeetCode problem, an implementation problem, an architecture or system design round and a behavioral round. System design was the hard part for them as a new grad.

The Software Engineering Intern (2027) posting asks for a fall 2027 or spring 2028 graduation and pays $54-$60 per hour in the SF Bay Area. A Mountain View intern in October 2025 had two LeetCode-style medium interviews with follow-ups, then a purely behavioral hiring manager interview.

Databricks interview questions by round

These come from 2025 candidate reports on Taro and the Databricks-tagged problem lists that candidates point to.

Round	Reported questions and topics
Technical screen	Design Hit Counter: record hits and return hits in the past five minutes with a sliding window, then write test cases (US, October 2025)
Onsite: algorithms	A bit manipulation problem that the 2025 hire called not obscure; tagged practice includes IP to CIDR and Task Scheduler
Onsite: coding or API	“Construct an API for a practical problem” (San Francisco new grad, October 2025); Design Tic-Tac-Toe is a common tagged design-style problem
Onsite: systems	Concurrency and data handling; a Databricks-tagged example is Web Crawler Multithreaded
Behavioral	Past projects and internships, why Databricks, fit with the culture principles

Asked across rounds: write tests yourself, explain complexity, and be ready for follow-ups once the first version works.

Databricks technical screen

A 60-minute live coding interview with an engineer. The October 2025 US candidate described a short introduction and then straight into one problem: implement a hit counter that returns the number of hits in the last five minutes, then write test cases to prove it. Expect to be asked about memory use when hits arrive in bursts and how you would make it thread-safe.

Databricks onsite: coding and systems rounds

The onsite is where Databricks differs from a plain LeetCode loop. One coding round is usually algorithmic. The other is implementation-heavy, such as designing a small API or class with state. The systems round tests how you reason about concurrency, memory and data volume, which fits a company whose product is a data and AI platform built on Apache Spark. The November 2025 hire who accepted an offer stressed that this round was “systems” rather than system design.

Databricks system design interview

For experienced hires and some new grads, the design round asks you to build a backend service and reason about scale. Prepare to talk about partitioning, caching, failure handling and how you would measure the system. Databricks does not publish prompts for this round, and candidate reports name only the API-construction task above.

Databricks behavioral round

Usually a hiring manager interview on past projects and internships. Databricks’ prep page says every candidate is assessed against the same core competencies, using “tell me about a time” prompts. The six culture principles are customer obsessed, raise the bar, truth seeking, first principles, bias for action and company first. Sample answers mapped to each are on the Databricks behavioral interview questions page.

Databricks platform interview questions for data engineers

DataCamp’s 2026 guide and similar lists cover the same core: Spark on Databricks, Delta Lake, Unity Catalog, the medallion architecture, Delta Live Tables and Photon.

Q: What does the Delta Lake transaction log do?

The _delta_log folder stores an ordered set of JSON commit files plus periodic Parquet checkpoints. Each commit records files added and removed. Readers reconstruct the table state from the log, which gives ACID transactions, optimistic concurrency for writers, schema enforcement and time travel to earlier versions on top of plain Parquet files.

Q: How is Unity Catalog different from the Hive metastore?

The Hive metastore is per workspace. Unity Catalog is account-level, so one catalog serves many workspaces, and it uses a three-level namespace of catalog.schema.table. It centralizes permissions, lineage and auditing, and governs files, volumes, models and functions as well as tables.

Q: Explain the medallion architecture.

Bronze holds raw ingested data as it arrived. Silver holds cleaned, deduplicated and conformed data. Gold holds business-level aggregates for reporting and ML. Each layer is a set of Delta tables, which makes it possible to reprocess from bronze if a transformation was wrong.

Q: When do you use OPTIMIZE, Z-ORDER or liquid clustering?

OPTIMIZE compacts many small files into fewer large ones. Z-ORDER co-locates related values so data skipping reads fewer files for filters on those columns. Liquid clustering replaces fixed partitioning and Z-ORDER on newer tables and lets you change clustering keys without rewriting the whole table. VACUUM removes files no longer referenced, which also limits how far back time travel can go.

Q: How do you handle a skewed join in Spark on Databricks?

Check the Spark UI for one task running far longer than the rest. If one side is small, broadcast it. Otherwise rely on adaptive query execution, which splits skewed partitions at runtime, or salt the hot key by adding a random suffix on the large side and exploding the matching keys on the other side.

Q: What is Auto Loader, and when would you use Delta Live Tables?

Auto Loader (the cloudFiles source) incrementally ingests new files from cloud storage with schema inference and evolution, tracking what it has processed. Delta Live Tables, now part of Lakeflow Declarative Pipelines, lets you declare tables and expectations (data quality rules) and have Databricks manage dependencies, retries and infrastructure, which suits pipelines you would otherwise orchestrate by hand with Jobs.

Databricks in India: Bengaluru

Databricks has an engineering presence in Bengaluru. Candidate reports from there on Taro and Glassdoor are mostly for senior and L4 software engineers, solutions architects and data roles rather than campus hiring, and they describe three to four technical rounds with DSA and system design. Most India searches for “Databricks interview questions” are about the platform; those questions are in the labelled section above.

What Databricks interviewers score

Working code with your own tests. Two 2025 reports describe interviewers asking for test cases after the solution.
Follow-up readiness. The 2025 intern and screen reports both describe follow-up questions after the main solution.
Systems sense. Concurrency, memory and scale come up even in rounds that are not called system design.
Evidence for the culture principles. Stories with data behind a decision (truth seeking) and a clear owner (bias for action) do better than general teamwork stories.

A four-week Databricks prep plan

Week 1: Databricks-tagged mediums: hit counter, tic-tac-toe, IP to CIDR, task scheduler. Write tests for each before checking the answer.
Week 2: Concurrency: a multithreaded crawler, a thread-safe LRU cache and a bounded blocking queue. Explain the race each lock prevents.
Week 3: One system design per day on data-heavy services (a metrics ingestion service, a job scheduler, a versioned key-value store). New grads should still do at least three.
Week 4: Behavioral stories mapped to the six principles, then two full mock onsites of four back-to-back hours.

Databricks pay in the US

The Software Engineer - New Grad (2027 Start) posting lists a base of $145,000-$155,000 in Zone 1 and $137,750-$147,450 in Zone 2 for the US, and $125,000-$130,000 for Canada. Databricks links a separate document that maps cities to zones. Total pay may include an annual performance bonus and equity. The 2027 intern posting lists $54-$60 per hour in the SF Bay Area.

Levels.fyi’s self-reported US medians for Databricks software engineers, including stock and bonus, are about $292,000 at L3 (entry), $427,000 at L4, $656,000 at L5 (senior) and $1.26 million at L6. Databricks is private, so equity value depends on its funding rounds and any future listing.

Frequently asked questions about Databricks interviews

What is the Databricks interview process for software engineers?

A recruiter call (about 20 minutes in a September 2025 Bellevue new grad report), a 60-minute technical screen with an engineer, then a virtual onsite of about four interviews. A US engineer who accepted an offer in November 2025 had DSA, a systems round (not system design), a coding round and a behavioral round; another US candidate in October 2025 had a LeetCode-style problem, an implementation problem, system design and behavioral. Databricks then runs reference checks before the offer.

How long does the Databricks hiring process take?

Databricks’ own interview prep page says the process typically takes two to three months, depending on the role, region and team. It targets feedback within 48 hours of your final interview and asks you to contact your recruiter if you have not heard within a week.

What questions are asked in the Databricks technical screen?

Usually one LeetCode-style problem that you implement and test live. An October 2025 US candidate had the hit counter design problem (count hits in the last five minutes with a sliding window) and was asked to write test cases. Databricks-tagged problems that come up in prep lists include Design Hit Counter, Design Tic-Tac-Toe, IP to CIDR and a multithreaded web crawler.

Does the Databricks new grad loop include system design?

Often, yes. A San Francisco new grad who reached the final round in October 2025 described four interviews including a system design component and a task to construct an API for a practical problem, and a US candidate who got an offer in October 2025 said system design was the hardest part as a new grad. Interns usually get two coding interviews and a hiring manager behavioral instead.

How much does Databricks pay new grad software engineers?

The Software Engineer - New Grad (2027 Start) posting lists $145,000-$155,000 in Zone 1 and $137,750-$147,450 in Zone 2 for the US, and $125,000-$130,000 for Canada, plus eligibility for an annual bonus and equity. Software engineering interns in the SF Bay Area are listed at $54-$60 per hour.

What are Databricks’ culture principles?

Databricks lists six: we are customer obsessed, we raise the bar, we are truth seeking, we operate from first principles, we bias for action, and we put the company first. Its interview prep page says every candidate is assessed against the same core competencies, using “tell me about a time” style behavioral questions.

Are Databricks interviews in person?

Databricks says interviews run virtually on Google Meet unless your recruiter tells you otherwise, and it recommends business casual dress, a clean background and testing screen sharing before the call.

Why does “Databricks interview questions” also bring up Spark and Delta Lake questions?

Many data engineers interview at other companies for roles that use the Databricks platform, and those interviews ask about Spark, Delta Lake, Unity Catalog and Databricks jobs. Those questions are different from the Databricks company loop, which is mostly coding, systems and behavioral rounds. A short labelled set of platform questions is on this page for data engineers.