Databricks Interview Questions

Databricks Interview Questions

Practice 131 real Databricks interview questions for 2026. Covers all top categories — Coding & Algorithms, System Design, Behavioral & Leadership, Statistics & Math, Software Engineering Fundamentals — across Software Engineer, Data Scientist, Machine Learning Engineer, and Data Engineer roles. Real questions from actual interviews with detailed solutions; this collection explains what’s distinctive about Databricks interviews, what interviewers evaluate, what to expect in each round, and how to structure your interview preparation. Expect a heavy software-engineering tilt: Software Engineer rounds repeatedly probe storage and data-platform design (hierarchical file systems, cache designs, lakehouse tradeoffs), distributed job scheduling and dependency-aware pipelines, concurrency and multithreaded systems (synchronous log writers, thread-safe KV stores), and performance-focused algorithmic problems and query optimizations. Data Scientist questions emphasize regression assumptions and coefficient transformations, similarity search across datasets, hypothesis testing and metric tradeoffs (ROC-AUC vs PR-AUC), and product-analytics counting problems. Machine Learning Engineer prompts focus on implementing algorithms (gradient descent, lazy arrays) and safety/OOM detection for models. Data Engineer coverage targets data-quality diagnostics, Spark/partitioning and pipeline performance. To prepare, prioritize timed coding practice, system-design sketches that show tradeoffs for data systems, concise statistics explanations, and polished STAR stories for behavioral rounds.

131 Questions 1 Company07.30.2026
Showing 20 results
Role
Databricks logo
Databricks
Hard
Software Engineer

Design Snapshot Set Iteration and Clarify Durable Writes

Work through a snapshot-set iterator and then explain how you would clarify a separate durable-writer exercise whose detailed contract has not been pr...

Software Engineering Fundamentals
15
0
157 people solved
Jul 26, 2026
Databricks logo
Databricks
Medium
Software EngineerSenior+

Design Chat Deletion Semantics Under Concurrent Sends

Design Chat Deletion Semantics Under Concurrent Sends Design the backend of a chat application that supports creating threads, sending messages, readi...

System Design
26
0
240 people solved
Jul 14, 2026
Databricks logo
Databricks
Hard
Software Engineer

Design a Music Playlist Service

Design a Music Playlist Service Design a service where users create playlists, add or remove tracks, reorder items, and retrieve a playlist in playbac...

System Design
7
0
65 people solved
Jul 25, 2026
Databricks logo
Databricks
Hard
Software Engineer

Design a Key-Value Store with Hit Counting

Design a Key-Value Store with Hit Counting Design an in-memory key-value store together with a hit-counter capability. The phrase "hit counter" is amb...

Software Engineering Fundamentals
5
0
63 people solved
Jul 25, 2026
Databricks logo
Databricks
Hard
Software Engineer

Design Chat APIs, Storage, and Core Message Flows

Design Chat APIs, Storage, and Core Message Flows Design the API and database model for a chat service. Cover direct and group conversations, sending ...

System Design
3
0
51 people solved
Jul 25, 2026
Databricks logo
Databricks
Medium
Software Engineer Locked

Design a Thread-Safe Buffered Writer with a Background Flush Thread

This question assesses a candidate's ability to design a concurrent, thread-safe component that decouples fast in-memory writes from slower disk I/O u...

System Design
75
0
874 people solved
Jun 23, 2026
Databricks logo
Databricks
Hard
Software EngineerSenior+

Design a Durable Concurrent Event Writer

Design a Durable Concurrent Event Writer Design a thread-safe DataWriter used by one application process on one server: `text DataWriter(file_path) pu...

System Design
11
0
104 people solved
Jul 7, 2026
Databricks logo
Databricks
Hard
Software EngineerSenior+

Implement Generalized Tic-Tac-Toe

Implement Generalized Tic-Tac-Toe Implement a TicTacToe class for two players on an m by n board with a configurable winning length k. `text TicTacToe...

Coding & Algorithms
15
0
149 people solved
Jul 7, 2026
Databricks logo
Databricks
Hard
Software EngineerSenior+

Build a Constant-Time Snapshot Set Iterator

Build a Constant-Time Snapshot Set Iterator Design SnapshotSet, a set of integers whose iterators observe an immutable logical snapshot without copyin...

Coding & Algorithms
8
0
90 people solved
Jul 7, 2026
Databricks logo
Databricks
Medium
Software EngineerSenior+

Implement a Concurrent Buffered File Logger

Implement a Concurrent Buffered File Logger Design a logger that accepts writes from many threads, buffers records, and appends them safely to one fil...

Software Engineering Fundamentals
1
0
12 people solved
Jul 30, 2026
Databricks logo
Databricks
Hard
Software EngineerSenior+

Discuss Motivation, Feedback, and Technical Disagreement

Discuss Motivation, Feedback, and Technical Disagreement Prepare concise, evidence-based responses to the following behavioral areas. Use real experie...

Behavioral & Leadership
3
0
36 people solved
Jul 7, 2026
Databricks logo
Databricks
Medium
Software EngineerSenior+

Detect a K-in-a-Row Win on a Rectangular Board

Detect a K-in-a-Row Win on a Rectangular Board Implement winning_move(board, row, col, k) after a valid move has placed a player's nonzero integer tok...

Coding & Algorithms
0
0
10 people solved
Jul 30, 2026
Databricks logo
Databricks
Medium
Software EngineerSenior+

Design an Online Book Seller Platform

Design an Online Book Seller Platform Design a service for browsing and searching books, managing inventory, placing orders, taking payments, and trac...

System Design
0
0
9 people solved
Jul 30, 2026
Databricks logo
Databricks
Medium
Frontend Engineer

Design a Collaborative Playlist Editor

Design a Collaborative Playlist Editor Design the data model and APIs for a playlist application. Authorized collaborators can add a song, remove a pl...

System Design
16
0
128 people solved
Jul 3, 2026
Databricks logo
Databricks
Medium
Software EngineerSenior+

Add Sliding-Window Get and Put Activity Metrics to a Key-Value Store

Add Sliding-Window Get and Put Activity Metrics to a Key-Value Store Extend an in-memory key-value store with averageGet(window) and averagePut(window...

Software Engineering Fundamentals
0
0
7 people solved
Jul 30, 2026
Databricks logo
Databricks
Medium
Software Engineer Locked

Design a Book Price Aggregator

This question evaluates skills in distributed systems design, fault tolerance, scalability, integration with external services, transactional consiste...

System Design
124
1
1247 people solved
May 6, 2026
Databricks logo
Databricks
Hard
Software Engineer

Design a single-node persistent in-memory cache

Scenario Design a single-machine in-memory cache used by a web service to serve concurrent read and write requests. This is a deliberately low-level s...

System Design
217
2
2295 people solved
Jan 22, 2026
Databricks logo
Databricks
Medium
Software Engineer

Design a Chat Application with a Partitioned Cache

Design a Chat Application with a Partitioned Cache Design an end-to-end chat application that supports direct conversations and small group conversati...

System Design
2
0
41 people solved
May 27, 2026
Databricks logo
Databricks
Medium
Software Engineer

Find the Earliest Anagram Window

Find the Earliest Anagram Window Problem Implement firstAnagramStart(text, pattern) -> index. Return the zero-based start index of the earliest contig...

Coding & Algorithms
1
0
18 people solved
Jun 29, 2026
Databricks logo
Databricks
Hard
Software EngineerSenior+

Design a Concurrent Key-Value Store with Batch Writes

Design a Concurrent Key-Value Store with Batch Writes Design the core implementation of an in-memory key-value store for concurrent callers. For this ...

Software Engineering Fundamentals
4
0
39 people solved
May 10, 2026

Frequently Asked Questions

How difficult are Databricks interviews?
Databricks interviews are generally high bar and tend to be more difficult than average because the company evaluates both deep algorithmic skill and domain-specific data-platform knowledge. For Software Engineer roles you should expect LeetCode-style algorithmic problems at medium-to-hard difficulty plus systems and concurrency prompts drawn from real platform work like cache design, job schedulers, multi-threaded log writers, and lazy data structures. Data Scientist interviews mix classical statistics and practical data-manipulation problems (linear-regression diagnostics, ROC vs PR tradeoffs, nearest-neighbor similarity), while ML Engineer and Data Engineer loops emphasize production ML and pipeline debugging respectively. Strong communication and tradeoff reasoning are required throughout.
What does the Databricks interview process look like and which roles and categories appear most often?
Databricks commonly uses a multi-stage process: recruiter screen, one or two technical screens (coding or ML/statistics), and a virtual onsite containing 3–5 interviews (coding, system/architecture, and behavioral/hiring-manager rounds). Coding and system-design questions dominate for Software Engineer candidates and often reference distributed-data themes such as Spark-style computation, Delta Lake consistency, job orchestration and storage/compute tradeoffs. Data Scientist loops focus on hypothesis testing, regression diagnostics, and scalable SQL or similarity searches. Machine Learning Engineer and Data Engineer interviews center on productionizing models, OOM and harmful-content detection, and diagnosing pipeline performance and data-quality issues.
What is a practical prep timeline before interviewing at Databricks?
A focused 6-week plan tends to work well: weeks 1–2 refresh core algorithms, data structures, and coding speed with timed problems; weeks 3–4 study distributed-data concepts, Spark/Delta basics, and system-design patterns relevant to job schedulers, caching, and storage-consistency tradeoffs; week 5 concentrate on role-specific skills—statistics and evaluation metrics for Data Scientists, gradient-descent and model-deployment for MLEs, pipeline debugging for Data Engineers; week 6 run full mock interviews, practice clear tradeoff explanations, and rehearse STAR behavioral stories showing impact and ownership. Adjust intensity based on experience and time available.
What key subtopics should I focus on for Databricks interviews?
Prioritize a short list that maps to the company’s product focus and the question breakdown: for engineers, algorithms, concurrency, and storage-oriented system design problems such as dependency-aware job schedulers, cache designs with hit-count tracking, multi-threaded log writers, and lazy-array/KV-store implementations; for data science, linear-regression assumptions, multicollinearity diagnosis, hypothesis testing, ROC-AUC vs PR-AUC tradeoffs, and nearest-neighbor similarity across datasets; for ML engineers, solid numerical optimization (gradient descent) and production safety (OOM and harmful-content detection); for data engineers, pipeline performance troubleshooting, partitioning, and data-quality diagnostics.
Any standout interview tips and common pitfalls to avoid at Databricks?
Show systems thinking: explain consistency, fault modes, cost/latency tradeoffs, and operational concerns (retries, backpressure, monitoring) when designing solutions. In coding rounds write clean, testable code and discuss complexity and edge cases. For data and ML questions, be explicit about metric choices, assumptions, and how data quality affects conclusions. Avoid common pitfalls like ignoring distributed constraints, skipping concurrency details, failing to justify design tradeoffs, or overfitting to toy metrics. Close each answer with a short summary of tradeoffs and next steps you would take in production to demonstrate ownership and pragmatism.

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