# Databricks interview process and top questions

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Source: https://www.aced.io/blog/databricks-interview-process
Source observed: 2026-11-05T02:19:26.018Z
Last checked: 2026-11-05T02:19:26.018+00:00
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# Get a Job at Databricks: Interview Process and Top Questions

[Databricks](https://www.aced.io/blog/tag/databricks) specializes in data and AI and hosts a data intelligence platform used by over 10,000 companies to unify and democratize data, analytics, and AI. Databricks is headquartered in San Francisco, offers hybrid and remote roles, and calls its employees “Bricksters.”

![Databricks office building](https://storage.ghost.io/c/a5/f5/a5f5c2f0-4c62-43c7-891b-662a0b6d68b3/content/images/2024/12/Databricks-Office-Building.jpeg)

Christy Umberger • Last updated a month ago

## Interview process

The process varies somewhat by role, typically takes about **one month**, and generally has three parts. Databricks typically responds within a couple of days after each round:

1. Recruiter phone screen
2. Technical screen
3. Final round of **4–5 loops**

### Recruiter phone screen

Discuss your background, resume, and basic qualifications. Prepare for “Why Databricks?”, describe a project you are proud of, research Databricks culture and technology, and bring questions.

### Technical screen

The technical screen is a **70-minute live coding challenge on CodeSignal** with four medium-to-hard questions, often two medium and two hard. Prepare for:

- Data structures and algorithms
- String processing and string manipulation
- [Graph search](https://www.aced.io/courses/software-engineering/swe-practice/graph-search?ref=exponent-blog.ghost.io)
- SQL and Python
- [Graphs](https://www.aced.io/courses/software-engineering/swe-practice/graphs?ref=exponent-blog.ghost.io)
- [Linked lists](https://www.aced.io/courses/software-engineering/swe-practice/reverse-linked-list?ref=exponent-blog.ghost.io)
- [Queues](https://www.aced.io/courses/software-engineering/swe-practice/stacks?ref=exponent-blog.ghost.io)

### Final round

The final round is on-site or virtual and consists of **4–5 one-hour interviews**. The mix depends on the role and normally includes one behavioral loop, one hiring-manager interview, and several technical loops covering domain-specific knowledge.

## Top Databricks interview questions

### Behavioral

- [Tell me about yourself.](https://www.aced.io/questions/104/tell-me-about-yourself?ref=exponent-blog.ghost.io)
- [Tell me about the accomplishment you are most proud of.](https://www.aced.io/questions/3018/proudest-accomplishment-interview-question?ref=exponent-blog.ghost.io)
- Describe the types of projects you have worked on.
- Why are you interested in Databricks?
- Describe a time when you were innovative in solving a problem.

### Coding

- [Demo LabelBox for an Autonomous Delivery Client.](https://www.aced.io/questions/4337/demo-labelbox-for-an-autonomous-delivery-client?ref=exponent-blog.ghost.io)
- Given an array of string commands, output a correct file path.
- Design an algorithm to get server load during the past five minutes from request timestamps.
- Create a load-tracking hashmap that returns average put/get calls per second during the last five minutes.

### System design

- [Design a distributed file system.](https://www.aced.io/questions/3257/design-distributed-file-system?ref=exponent-blog.ghost.io)
- [Design a system like YouTube.](https://www.aced.io/questions/2701/design-system-like-youtube?ref=exponent-blog.ghost.io)
- Design a data lake for large amounts of streaming and batch data.
- Design a machine-learning pipeline for large datasets and automated model training and deployment.
- Design a system for data consistency and fault tolerance in a distributed environment.

### Machine learning

- [Explain training and testing data.](https://www.aced.io/questions/4347/training-testing-data?ref=exponent-blog.ghost.io)
- [How do you ensure a deployed model remains up to date?](https://www.aced.io/questions/3741/maintaining-updated-deployed-model?ref=exponent-blog.ghost.io)
- [How can we tell when a model needs to be refreshed?](https://www.aced.io/questions/4350/model-refresh?ref=exponent-blog.ghost.io)
- [What is the importance of feature scaling and normalization?](https://www.aced.io/questions/4348/feature-scaling-normalization?ref=exponent-blog.ghost.io)
- [What are the advantages and limitations of linear regression?](https://www.aced.io/questions/4360/advantages-and-limitations-of-linear-regression?ref=exponent-blog.ghost.io)
- [What is the difference between classification and regression?](https://www.aced.io/questions/4349/classification-vs-regression?ref=exponent-blog.ghost.io)

### Data science

Prepare statistics, forecasting, data-science concepts, linear regression, SQL, window functions, Python, machine-learning concepts, and Spark queries. Resources include [statistics](https://www.aced.io/courses/data-science/statistics-experimentation-questions/statistics-experimentation-intro?ref=exponent-blog.ghost.io), [linear regression](https://www.aced.io/courses/data-science/statistics-experimentation-questions/linear-regression-intro?ref=exponent-blog.ghost.io), [SQL](https://www.aced.io/courses/data-science/sql-interviews/how-to-answer-sql-interview-questions?ref=exponent-blog.ghost.io), [window functions](https://www.aced.io/courses/data-science/sql-interviews/window-functions?ref=exponent-blog.ghost.io), and [ML concepts](https://www.aced.io/courses/data-science/ml-concepts-questions-data-scientists/ml-concepts-intro?ref=exponent-blog.ghost.io).

### Product management

- [Prioritize and structure roadmaps.](https://www.aced.io/questions/3019/prioritize-structure-roadmaps-interview-question?ref=exponent-blog.ghost.io)
- [Gather health data for deployed microservices.](https://www.aced.io/questions/1686/gather-health-data-deployed-microservices?ref=exponent-blog.ghost.io)
- [Debug a metric that was off by x percentage.](https://www.aced.io/questions/1685/debugging-metric-off-by-x-percentage?ref=exponent-blog.ghost.io)
- What is a favorite product of yours, and how would you improve it?
- What is the difference between handling projects and handling products?

## Interview loops explained

### Behavioral

A behavioral loop is part of every candidate’s final round. It assesses culture and team fit through past experience, collaboration, and problem-solving questions from senior team members. Use the [STAR method](https://www.aced.io/blog/what-is-the-star-method-and-how-to-use-it-during-interviews?ref=exponent-blog.ghost.io) with specific examples and study [Databricks’ core values](https://www.databricks.com/company/careers/culture?ref=exponent-blog.ghost.io): customer obsessed, raise the bar, truth seeking, operate from first principles, bias for action, and put the company first.

### Coding

The coding final round is deeper, more role-specific, more interactive, and closer to real-world Databricks problems than the technical screen. Expect live coding involving distributed systems, big data, Spark, and algorithms. Explain your reasoning, trade-offs, edge cases, optimization, and follow-up answers. Prepare with the [Aced Software Engineering Interviews course](https://www.aced.io/courses/software-engineering?src=nav&ref=exponent-blog.ghost.io).

### System design

Expect a live whiteboard interview designing a scalable system. Emphasize communication, iteration after feedback, and follow-up questions. Prepare distributed systems, scalability, storage, data pipelines, cloud architecture, Apache Spark, and Delta Lake. Use the [Aced System Design Interviews course](https://www.aced.io/courses/system-design-interviews?src=nav&ref=exponent-blog.ghost.io).

### Machine learning

Expect an ML case study and ecosystem-specific ML questions. A case study may provide a dataset and problem requiring you to train an appropriate model. Study Apache Spark, Delta Lake, MLflow, algorithms, scalability, deployment, monitoring, evaluation, and big data. Prepare with the [Aced Machine Learning Engineer Interviews course](https://www.aced.io/courses/ml-engineer?src=nav&ref=exponent-blog.ghost.io).

### Data science

Expect a data case study and conversational assessment involving large datasets, statistics, and [A/B testing](https://www.aced.io/courses/data-science/statistics-experimentation-questions/answer-ab-test-questions?ref=exponent-blog.ghost.io). Clarify decisions, explain your analysis, present the case study, and handle follow-ups. Practice Python, SQL, R, Pandas, and PySpark. Use the [Aced Data Science Interviews course](https://www.aced.io/courses/data-science?src=nav&ref=exponent-blog.ghost.io).

### Product management

The PM interview includes a take-home case study, presentation, conversational interview, and technical assessment. Show customer-first thinking, data-driven decisions, vision, and clear reasoning. Prepare STAR examples about leading initiatives, resolving conflict, and aligning teams. Technical topics include data pipelines, ETL, distributed systems, machine-learning workflows, cloud platforms, and Spark. Use the [Aced Product Management Interviews course](https://www.aced.io/courses/pm?src=nav&ref=exponent-blog.ghost.io).

## Interview tips

- **Know Databricks inside and out:** study its [company information](https://www.databricks.com/company/about-us?ref=exponent-blog.ghost.io), [data platform](https://www.databricks.com/product/data-intelligence-platform?ref=exponent-blog.ghost.io), and [current ventures](https://www.databricks.com/databricks-ventures?ref=exponent-blog.ghost.io).
- **Prepare for rigorous technical interviews:** expect domain deep dives and tasks similar to the role’s daily work; study complex topics.
- **Show problem-solving, adaptability, and collaboration:** demonstrate technical depth, real-world problem solving, growth mindset, communication, and relationship-building.

## FAQs

### How should I prepare?

Practice coding and technical questions, learn Databricks’ culture, values, platform, and products, demonstrate communication and growth mindset, and bring questions.

### Does Databricks offer remote work?

Yes. Many roles are hybrid, balancing remote work with weekly team days in the office, and some are fully remote. See [Databricks Open Positions](https://www.databricks.com/company/careers/open-positions?ref=exponent-blog.ghost.io).

### Does Databricks hire students or new graduates?

Yes. Databricks hires new graduates and offers **12–16-week internships**, typically in San Francisco, Mountain View, Bellevue, Amsterdam, Berlin, Belgrade, or Bangalore. New-graduate roles usually open around August. Interns are described as current undergraduate or graduate computer-science students who understand deep learning and are proficient with PyTorch software engineering. See [Databricks Internships and Early Careers](https://www.databricks.com/company/careers/university-recruiting?ref=exponent-blog.ghost.io).

## More Databricks preparation

- [Browse Databricks interview questions](https://www.aced.io/questions?company=databricks&src=blog) and answers from real candidates.
- [Book time with a Databricks coach](https://www.aced.io/coaching?company=databricks): mock interviews, career coaching, and resume review. [Browse coaches](https://www.aced.io/coaching?company=databricks&src=blog).
- We advertise a **96% rating from 5,400 reviews** and offer [a free account](https://www.aced.io/signup?src=blog) with interview guides, insider tips, and courses.

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