Databricks Interview Questions, Process & Experiences (2026)
Updated by Databricks candidates
Databricks builds a data intelligence platform for data, analytics, and AI, and its technical interviews are known for being rigorous. Expect medium to hard coding questions and technical rounds built around Spark, Delta Lake, and big data.
Databricks interview process
Databricks' interview process typically takes about a month, with 3 main stages that change slightly by role. Databricks responds quickly, so expect to hear back within a couple of days of each round.
The process runs in this order:
Recruiter phone screen
Databricks' recruiter phone screen covers your background, resume, and basic qualifications. Prepare to answer "Why Databricks?" and walk through a past project you're proud of.
Research Databricks' culture and technology before the call, and bring questions that show your interest.
Technical screen
Databricks' technical screen is a 70-minute live coding challenge on CodeSignal. It has 4 questions from medium to hard, often 2 of each.
Prepare for these topics:
- Data structures and algorithms
- String processing and manipulation
- Graph search
- Graphs
- Linked lists
- Queues
- SQL and Python
Final round
Databricks' final round includes 4 to 5 one-hour interviews, held onsite or virtually, and the mix varies by role. Expect 1 behavioral interview, 1 hiring manager interview, and several technical interviews on your domain.
Databricks interview loops
Behavioral
Every Databricks final round includes a behavioral interview on culture and team fit. Expect questions about your past experience, collaboration, and problem-solving approach.
A panel of senior team members asks strategic, high-level questions. Use the STAR method to organize your answers with specific examples.
Tailor your answers to Databricks' core values:
- We are customer obsessed
- We raise the bar
- We are truth seeking
- We operate from first principles
- We bias for action
- We put the company first
Coding
Databricks' coding final round goes deeper than the technical screen. It's more role-specific, more interactive, and built around real Databricks challenges.
You'll code live on 1 or more complex challenges tied to Databricks' stack, such as distributed systems, big data, Spark, and algorithms.
Talk through your thought process, trade-offs, edge cases, and optimizations, and expect follow-up questions. Practice with our Software Engineering Interviews course.
System design
Databricks' system design interview is fairly standard: you'll design a scalable system in a live whiteboard interview. Explain your approach and thought process as you design.
Expect a system tied to Databricks' work, such as distributed systems, scalability, data storage, data pipelines, or cloud architecture. Be ready to iterate on your design based on live feedback and answer follow-up questions.
Before your system design interview, get familiar with Databricks' platform and technologies, such as Apache Spark and Delta Lake. Practice with our System Design Interviews course.
Machine learning
Databricks' machine learning interview includes an ML case study and questions on ML concepts tied to the Databricks ecosystem. In the case study, you may get a dataset and a problem, then train a model to solve it.
For the discussion, study ML fundamentals and how Databricks uses Apache Spark, Delta Lake, and MLflow. Focus on ML algorithms, scalability, model deployment, monitoring, evaluation, and big data.
Practice with our Machine Learning Engineer Interviews course.
Data science
Databricks' data science interview includes a data case study and a conversational assessment on large datasets, statistics, and A/B testing. For the case study, you'll get a dataset and a problem statement.
As you analyze and present, explain your decisions and problem-solving, and prepare for follow-up questions or new constraints. Study Databricks' platform, technology, and current work so you're ready for practical questions.
Work through Python, SQL, R, Pandas, and PySpark, and practice with our Data Science Interviews course.
Product management
Databricks' product management interview includes a take-home case study, a case study presentation, a conversational interview, and a technical assessment. In the case study, show customer focus, decisions backed by data, and product vision, and explain your thought process clearly.
For the conversational interview, prepare STAR method examples about leading initiatives, resolving conflicts, or aligning teams. The technical assessment tests big data concepts (data pipelines, ETL, distributed systems, ML workflows), cloud platforms, and Spark.
Practice with our Product Management Interviews course.
Databricks interview questions(43)
These are interview questions asked during Databricks interviews, reported by real candidates. Last updated Oct 2026.
Behavioral
- “Tell me about yourself.” View 128 answers
- “Tell me about your past projects.” View 4 answers
- “Tell me about a time when you had to make a decision quickly.” View 7 answers
- “Walk me through your resume.” View 1 answer
- “Why do you want to be a Product Manager?” View 8 answers
Data Pipeline Design
- “Design a document processing pipeline.” View 8 answers
- “What's the difference between a data lakehouse and a data warehouse?” View 5 answers
- “How would you handle slow query performance for a single-user SQL endpoint in Databricks, where all sequentially run queries are affected?” See question
- “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?” View 2 answers
- “What is a Medallion Architecture?” View 2 answers
Machine Learning
- “Explain how RAG works.” View 5 answers
- “Describe your experience with LLMs.” See question
- “Explain transformers.” See question
- “What is a neural network?” See question
Analytical
- “You're a PM at United Airlines. How would you identify and solve the biggest problem in the post-booking experience?” View 3 answers
- “How do you forecast demand for a new product with no historical data?” See question
- “Debug a metric that was off by x percentage.” View 1 answer
Databricks interview tips
- Know Databricks well: Learn as much as you can about Databricks, its data platform, and its current ventures. Databricks looks for candidates who can contribute quickly and show real interest in the company.
- Prepare for rigorous technical interviews: Your technical interviews count the most at Databricks, with in-depth domain questions and tasks like your day-to-day work. Study more advanced topics than you would for most other companies.
- Show problem-solving, adaptability, and collaboration: Databricks looks for strong technical knowledge, a growth mindset, and clear communication. Show those skills in every interview, and highlight relationships you've built across teams.
- Cover the prep basics: Practice coding and technical questions, and expect in-depth questions about the company. Bring your own questions to show your interest.
Databricks interview guides(1)
Databricks Forward Deployed Engineer Interview Guide
Updated Oct 2026Databricks candidate interview experiences(14)
Forward Deployed Engineer
Feb 2026“When I went through Databricks, it honestly felt like a Palantir-style FDE loop had been transplanted over. The decomp round was so vague that if I skipped stakeholder questions and KPIs and jumped into architecture, I would have been dead.”
Forward Deployed Engineer
Oct 2026“The interview process was overall great. It was very structured and didn't have a Leetcode which I think is kind of stupid in 2026. I liked the questions and they were good ways to test an FDE. The interviewers and HR communication was extremely good. I would have liked a bit more clarity about the technical round especially in terms of the expectations, and sometimes it feels too easy and...”
Forward Deployed Engineer
Oct 2026“Databricks tries to prepare you well by giving very elaborate instructions on what to expect and how to prepare”
Product Manager
Sep 2026“The process was quite straightforward. I had time to work on my PRD assignment and the guidelines were helpful. The only thing is that because you only get a week to complete it, the work can be vigorous. ”
