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Databricks

5 rounds3-6 weeks8 patterns40% hard

This guide tracks 8 patterns (2 of them typically hard), 4 commonly reported questions, and a 5-round loop that usually runs 3-6 weeks.

Key patterns

Showing 3 of 8
1arrays hashing
medium85%
2dp 1d
hard80%
3dp 2d
hard70%
4bfs
medium75%
5trees
medium70%

Common questions

Showing 3 of 4
Design Distributed Data Processingvery common
Design Data Pipelinecommon
Distributed Sortcommon

Interview process

Showing 1 of 5 rounds
1. Technical screen60 min
codingdata-systems
2. Algorithms round60 min
algorithmsoptimization

Quick facts

Pacemoderate
Optimal requiredyes
Hints givenrarely

Insider tips

1/4
  • ·Strong focus on distributed systems

Compensation (TC)

Entry$XXX,XXX
Mid$XXX,XXX
Senior$XXX,XXX

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Databricks runs 5 rounds over 3-6 weeks. A free account unlocks the rest of this guide and a full practice round against the AI interviewer.

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Every lesson below is a free public reading page. No sign-up, no install, and the worked examples run in the tab.

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How Databricks judges you outside the code

The values and engineering norms the interviewers are calibrated against. Useful for the behavioral round, and useful for deciding which trade-off to argue for in the technical one.

Values they name

  • Customer Obsession - customers are the reason we exist
  • Ownership - act on behalf of the company
  • Relentless Innovation - push the boundaries
  • Data Driven - let data inform decisions
  • Transparency - open and honest communication

What they look for in behavioral rounds

  • Demonstrate deep technical expertise in data systems
  • Show passion for data and analytics platforms
  • Exhibit strong problem-solving with distributed systems
  • Display ability to work on complex, hard problems
  • Show customer-focused mindset in technical decisions

How the team builds

  • Founded by Apache Spark creators - data is in the DNA
  • Lakehouse architecture is the vision
  • ML and AI are first-class citizens
  • Distributed systems expertise expected
  • Open source contribution is encouraged

Primary stack

  • Scala
  • Java
  • Python
  • Apache Spark
  • Delta Lake
  • MLflow
  • Kubernetes
Code review
thorough reviews with performance focus
Deployment
staged rollouts with comprehensive testing
Documentation
strong documentation culture, especially for APIs

Reading the guide is the easy part. Databricks will ask you to perform.

CodeSparring is a practice environment, not a question bank. You sit a full round against an AI interviewer, in an editor that runs your code, and you leave with a score and a specific next rep.

An interviewer that reacts

Carry one problem from clarifying questions through to working code while an AI interviewer responds to what you say and what you type, by voice or by text.

Code that actually runs

An editor in the page with a real runtime and real test cases. You run your solution and read the output, the same way you would in a shared editor on the day.

A scored round, not a vibe

Every session ends with a rubric covering problem solving, communication, and code quality, so you can see which part of the round is costing you the offer.

And 364 lessons you can read right now, free

The whole curriculum is public. Read the concept, run the worked example in the tab, and only sign in when you want the graded exercise at the end of a lesson.

Start a practice round