Databricks interview questions. 13 from past candidates.
The process at Databricks, what each stage actually tests, and how candidates prep. Real questions where we have them, likely questions where we don't.
Scoutify watches Databricks's careers page around the clock. Browse the job board free. Alerts from $5/week.
[01] BY THE NUMBERS
Headline facts before you prep.
Pulled straight from Databricks's career page and public data sources. Tap any cell for the full breakdown.
Full Databricks company profile[02] INTERVIEW PROCESS
Standard software engineering loop at Databricks.
The stages below describe the typical SWE loop. Product, Design, and Data loops differ; pick a role to see how it changes, or jump straight to real questions reported for that role.
01Recruiter / Hiring Manager Screen
30-45 min
Recruiter / Hiring Manager Screen
30-45 minDiscussion of your background, research interests, and the role. ML roles often include a quick technical discussion about your past work.
- Be prepared to discuss your papers or projects in detail
- Know the company's recent publications or product launches
- Ask about the team's current research direction
02Technical Screen
60 min
Technical Screen
60 minCoding plus ML concepts. May include implementing an ML algorithm from scratch or discussing model architecture choices.
- Know how to implement common algorithms: logistic regression, decision trees, k-means
- Brush up on gradient descent, backpropagation, and loss functions
- Be comfortable coding in Python with NumPy
03ML Deep Dive
60 min
ML Deep Dive
60 minExtended discussion of ML concepts, model evaluation, feature engineering, and production ML challenges.
- Know bias-variance tradeoff, overfitting mitigation, and model selection
- Be ready to discuss model monitoring and data drift
- Understand the full ML lifecycle, not just training
04System Design / ML Architecture
60 min
System Design / ML Architecture
60 minDesign an ML system end-to-end: data pipeline, feature store, model training, serving, and monitoring.
- Practice designing recommendation systems, search ranking, and fraud detection
- Discuss feature engineering, online vs. offline serving
- Consider model freshness, A/B testing, and rollback strategies
05Research Discussion / Paper Review
45-60 min
Research Discussion / Paper Review
45-60 minSome companies ask you to present your research or discuss a recent paper. Tests depth of understanding and ability to communicate complex ideas.
- Choose a paper you understand deeply, not just superficially
- Be ready to discuss limitations and potential improvements
- Practice explaining technical concepts to different audiences
[03] REAL QUESTIONS
Reported by people who interviewed at Databricks.
13 questions sourced directly from candidates on Reddit, Blind, Glassdoor, and Scoutify user reports.
Other Roles
9 questions · 8 reported · 1 likely
Other Roles
9 questions · 8 reported · 1 likelyWhat's the difference between a data lakehouse and a data warehouse?
How would you handle slow query performance for a single-user SQL endpoint in Databricks, where all sequentially run queries are affected?
Design a database schema for a fitness app.
How would you handle scheduling dependencies between two nightly Jobs to ensure the second Job does not fail if the first Job runs longer than expected?
What is a Medallion Architecture?
How would you handle a task in a nightly job that fails unexpectedly during 10 percent of the runs?
When should you use Delta Live Tables over standard data pipelines built on Spark and Delta Lake?
When should you use a job cluster instead of an all-purpose cluster?
How do you see the integration of data analytics and AI evolving in the next few years, and what role do you believe Databricks will play in this evolution?
Data Science & Analytics
4 questions · 1 reported · 3 likely
Data Science & Analytics
4 questions · 1 reported · 3 likelyDatabricks aims to unify and democratize data for organizations. How do you envision your role contributing to this mission as a Senior Data Scientist?
Given Databricks's focus on building AI infrastructure, can you discuss your experience with machine learning frameworks and how they can be integrated into a data platform?
Can you describe your experience with Apache Spark, which is a key component of Databricks's platform, and how you've leveraged it to solve complex data problems?
Software Engineering
3 questions · 1 reported · 2 likely
Software Engineering
3 questions · 1 reported · 2 likelyDesign a document processing pipeline.
What aspects of Databricks's engineering culture do you find most appealing, and how do you see them influencing your career path in the company?
As a Sr. Manager of Engineering at Databricks, what strategies would you implement to foster a culture of customer obsession within your team?
Product Management
3 questions · 1 reported · 2 likely
Product Management
3 questions · 1 reported · 2 likelyHow do you prioritize and structure roadmaps, deciding what to build and when?
In the context of building a scalable data infrastructure at Databricks, what are some best practices you would advocate for to ensure high availability and performance?
Databricks provides solutions for financial services. What specific challenges do you think data teams face in this sector, and how could you help address them in the role of Manager, Delivery Solutions Architects?
TPM
2 questions · all reported by candidates
TPM
2 questions · all reported by candidatesDevOps
1 question
DevOps
1 questionDatabricks emphasizes innovation in AI and analytics. What unique perspectives or experiences do you bring that align with this direction as a Senior Designated Support Engineer?
HR
1 question
HR
1 questionThe Analyst position in Talent Acquisition Operations requires an understanding of data-driven hiring. How would you apply Databricks's tools to improve recruitment processes?
How to answer these: the STAR method
Use the STAR method: describe the Situation, the Task you faced, the specific Action you took, and the measurable Result. Aim for 60-90 seconds with one concrete metric. Practice it out loud before the interview so it flows naturally; the same structure works for every question above.
[04] CODING PRACTICE
LeetCode tagged for Databricks.
The 15 highest-frequency problems candidates report being asked in Databricks loops, pulled from the public company-wise question bank.
Medium
What it testsTrees
Why it appearsPulled from the public company-wise question bank, with a frequency score of 1.2 for Databricks. Acceptance rate 43.6% on LeetCode.
Open problem #742 on LeetCodeMedium
Why it appearsPulled from the public company-wise question bank, with a frequency score of 1.0 for Databricks. Acceptance rate 47.5% on LeetCode.
Open problem #380 on LeetCodeHard
Why it appearsPulled from the public company-wise question bank, with a frequency score of 1.0 for Databricks. Acceptance rate 32.0% on LeetCode.
Open problem #41 on LeetCodeMedium
What it testsTrees
Why it appearsPulled from the public company-wise question bank, with a frequency score of 0.9 for Databricks. Acceptance rate 45.3% on LeetCode.
Open problem #314 on LeetCodeMedium
Why it appearsPulled from the public company-wise question bank, with a frequency score of 0.7 for Databricks. Acceptance rate 34.6% on LeetCode.
Open problem #722 on LeetCodeMedium
Why it appearsPulled from the public company-wise question bank, with a frequency score of 0.7 for Databricks. Acceptance rate 45.9% on LeetCode.
Open problem #1242 on LeetCodeMedium
Why it appearsPulled from the public company-wise question bank, with a frequency score of 0.5 for Databricks. Acceptance rate 24.7% on LeetCode.
Open problem #91 on LeetCodeHard
Why it appearsPulled from the public company-wise question bank, with a frequency score of 0.4 for Databricks. Acceptance rate 34.6% on LeetCode.
Open problem #218 on LeetCodeMedium
Why it appearsPulled from the public company-wise question bank, with a frequency score of 0.3 for Databricks. Acceptance rate 30.3% on LeetCode.
Open problem #614 on LeetCodeHard
What it testsSliding window
Why it appearsPulled from the public company-wise question bank, with a frequency score of 0.2 for Databricks. Acceptance rate 43.0% on LeetCode.
Open problem #239 on LeetCodeMedium
What it testsTrees, Linked lists
Why it appearsPulled from the public company-wise question bank, with a frequency score of 0.1 for Databricks. Acceptance rate 59.1% on LeetCode.
Open problem #426 on LeetCodeHard
Why it appearsPulled from the public company-wise question bank, with a frequency score of 0.1 for Databricks. Acceptance rate 34.1% on LeetCode.
Open problem #381 on LeetCodeMedium
What it testsTrees
Why it appearsPulled from the public company-wise question bank, with a frequency score of 0.1 for Databricks. Acceptance rate 36.6% on LeetCode.
Open problem #987 on LeetCodeHard
Why it appearsPulled from the public company-wise question bank, with a frequency score of 0.1 for Databricks. Acceptance rate 48.9% on LeetCode.
Open problem #42 on LeetCodeEasy
What it testsArrays + hashing
Why it appearsPulled from the public company-wise question bank, with a frequency score of 0.0 for Databricks. Acceptance rate 51.4% on LeetCode.
Open problem #350 on LeetCode[05] HIRING PULSE
Databricks's hiring pulse.
We re-scan Databricks's career page every few minutes and keep the full posting history, so these counts come from the board itself, not an aggregator.
Posted (7d)
51
Posted (30d)
169
Posted (90d)
620
Scanned every few minutes · newest tracked posting May 22, 2026
[06] SALARY SNAPSHOT
Know the bands before the loop.
Median total compensation at Databricks by level, as reported by employees on Levels.fyi. Worth knowing before the recruiter asks about expectations.
Data Scientist
Source: Levels.fyi| Level | Total | Base | N |
|---|---|---|---|
| L4 | $174K | $174K | 2 |
| L3 | $245K | $150K | 5 |
| L6 | $529K | $256K | 2 |
Product Manager
Source: Levels.fyi| Level | Total | Base | N |
|---|---|---|---|
| L3 | $237K | $139K | 5 |
| L4 | $257K | $180K | 3 |
| L5 | $354K | $200K | 11 |
| L6 | $638K | $222K | 6 |
| L7 | $852K | $277K | 4 |
| L8 | $1376K | $340K | 3 |
Source: Levels.fyi · median of reported samples · N = sample count
Full compensation breakdown on the Databricks company page[07] AFTER YOU APPLY
What happens after you hit submit.
Scoutify sent 18 applications to Databricks for 11 users in the last 12 months, then watched what came back. Not survey answers; observed outcomes.
Get a screen
0%
share of applications
Reach an interview
0%
share of applications
Median cycle length (apply to terminal outcome): 8 days.
Based on 18 applications from 11 Scoutify users · last 12 months
[08] APPLY LOGISTICS
Applications go through Greenhouse.
Databricks runs hiring on Greenhouse, so the application form and recruiter follow-ups flow through it. Use the same email everywhere and keep the profile fields consistent with your resume; recruiters see both side by side.
The leading applicant tracking system for growing companies. Greenhouse powers structured hiring at thousands of organizations, from startups to enterprises.
Because Databricks hires through Greenhouse, you can auto-apply to new Databricks jobs with Sniper, which submits the Greenhouse form for you minutes after a matching role posts. Sniper sends one application per posting, and the employer's confirmation email for most applications lands in Scoutify Mail.
[09] PEOPLE ALSO ASK
Common questions about Databricks interviews.
Does Databricks sponsor H1B visas?
Yes, Databricks does sponsor H1B visas for international candidates. This support is crucial for attracting top talent from around the globe, allowing you to join a diverse and innovative team. It's advisable to discuss visa sponsorship during the interview process to understand the specifics of your situation.
What is the average salary and compensation structure at Databricks?
The average salary range for positions at Databricks is between $185,528 and $255,950, based on job postings with disclosed salaries. For higher-level roles, median total compensation can reach up to $1,652,975 for L7 positions. This competitive compensation structure reflects the company's commitment to attracting and retaining top talent in the data and AI fields.
What can I expect from the interview process at Databricks?
The interview process at Databricks typically involves multiple stages, including technical assessments and behavioral interviews. You may be asked to provide specific examples from your experience, such as how you've influenced technical strategies or utilized AI tools in previous roles. Preparing for questions that focus on your practical knowledge and problem-solving skills will be beneficial.
What is the current hiring volume and what roles are open right now at Databricks?
Databricks is actively hiring, with 1,504 job postings available. Some of the top roles currently open include 24 positions for Resident Solutions Architect and Solutions Architect, as well as 20 openings for Sr. Solutions Engineer and AI Engineer - FDE. This high volume of hiring suggests robust growth and opportunities for new employees.
[10] OVERVIEW
What candidates run into at Databricks.
AI company interviews blend traditional software engineering with ML-specific evaluations. Expect deep dives into ML fundamentals, statistics, paper discussions, and practical implementation challenges.
[11] PREP TIPS
How candidates prepare.
[12] EXPERT FRAMEWORKS
Frameworks and sample answers from interview coaches.
Curated from Columbia Engineering's licensed BigInterview library: expert-written tips, sample answers, and walkthroughs that work for any interview.
Source: BigInterview (licensed by Columbia Engineering)
[13] FAQ
Questions candidates ask about Databricks interviews.
Salary, visa sponsorship, process, hiring volume. Drawn from public data on Databricks.
Yes, Databricks does sponsor H1B visas for international candidates. This support is crucial for attracting top talent from around the globe, allowing you to join a diverse and innovative team. It's advisable to discuss visa sponsorship during the interview process to understand the specifics of your situation.
[14] MORE INTERVIEW PREP
Companies candidates compare with Databricks.
PREP SMARTER. APPLY FASTER.
Ready for Databricks? Let Scoutify keep your pipeline full.
Auto-apply to matching jobs so your search doesn't stop while you interview.
START FREEBrowse free. Alerts from $5/week, auto-apply from $15.