# Software Engineer
**Role:** Software Engineer · **Level:** L3
**Company:** [Databricks](https://scaleengineer.com/companies/databricks)
**Difficulty:** Medium
**Salary:** US$90000 - US$130000
**Experience:** 1 - 3
**Timeline:** ~7 days
The interview process for a Software Engineer (L3) at Databricks is designed to assess a candidate's foundational technical skills, problem-solving abilities, and cultural fit within the company. The process typically involves multiple rounds, starting with an HR screening, followed by technical interviews focusing on data structures, algorithms, and coding, and concluding with a behavioral and system design interview. The goal is to identify candidates who can contribute effectively to Databricks' innovative and collaborative environment.
Canonical: https://scaleengineer.com/interviews/databricks/l3-software-engineer
---
## Overall evaluation

- Technical Skills
- Communication and Behavioral

## Questions asked

- Given an array of integers, find the contiguous subarray with the largest sum.
- Implement a function to reverse a linked list.
- Design a URL shortening service.
- Tell me about a time you faced a technical challenge and how you overcame it.
- How would you handle a situation where a teammate is not pulling their weight?
- Explain the difference between a process and a thread.
- Write a function to find the kth smallest element in an unsorted array.
- How do you ensure the scalability of a web application?
- Describe a project where you had to collaborate with cross-functional teams.
- What are your strengths and weaknesses?

## Preparation tips

### lists

- Review fundamental data structures (arrays, linked lists, trees, graphs, hash maps) and algorithms (sorting, searching, dynamic programming, graph traversal).
- Practice coding problems on platforms like LeetCode, HackerRank, focusing on medium-difficulty problems.
- Understand Big O notation for time and space complexity analysis.
- Brush up on object-oriented programming (OOP) principles.
- Study basic system design concepts, such as scalability, availability, and fault tolerance.
- Prepare for behavioral questions by thinking about your past experiences using the STAR method (Situation, Task, Action, Result).
- Research Databricks' products, mission, and recent news.
- Prepare questions to ask the interviewer about the role, team, and company culture.

### studyPlan

- {"title":"Data Structures and Algorithms Fundamentals","longDescription":"Weeks 1-2: Focus on core data structures like arrays, linked lists, stacks, queues, hash maps, trees (binary trees, BSTs, heaps), and graphs. Practice implementing these and solving problems related to them. Understand their time and space complexities. Cover basic algorithms like sorting (quicksort, mergesort), searching (binary search), and recursion.","shortDescription":"Weeks 1-2: Data Structures (Arrays, Lists, Trees, Graphs, Hash Maps) & Basic Algorithms (Sorting, Searching, Recursion)."}
- {"title":"Algorithm Practice and Complexity Analysis","longDescription":"Weeks 3-4: Dive deeper into algorithms, including dynamic programming, graph traversal (BFS, DFS), greedy algorithms, and string manipulation. Practice medium-level coding problems on platforms like LeetCode, focusing on identifying the appropriate data structure and algorithm for a given problem. Analyze the time and space complexity of your solutions.","shortDescription":"Weeks 3-4: Advanced Algorithms (DP, Graph Traversal, Greedy) & Coding Practice (Medium LeetCode)."}
- {"title":"System Design Basics","longDescription":"Week 5: Focus on system design fundamentals. Understand concepts like scalability, availability, load balancing, caching, databases (SQL vs. NoSQL), and API design. Study common system design interview patterns and practice designing simple systems.","shortDescription":"Week 5: System Design Fundamentals (Scalability, Caching, Databases, APIs)."}
- {"title":"Behavioral Preparation and Company Research","longDescription":"Week 6: Prepare for behavioral questions. Reflect on your past experiences and prepare stories using the STAR method for common behavioral prompts (teamwork, challenges, failures, successes). Research Databricks' values and culture to align your answers.","shortDescription":"Week 6: Behavioral Questions (STAR Method) & Company Research."}
- {"title":"Final Review and Practice","longDescription":"Week 7: Mock interviews, review weak areas, and finalize questions to ask the interviewer. Ensure you are comfortable discussing your resume and projects in detail.","shortDescription":"Week 7: Mock Interviews, Review, Final Questions."}

## Location differences

- {"location":"Remote/Hybrid","differences":{"tips":["Highlight projects where you demonstrated adaptability and quick learning.","Emphasize your experience with remote collaboration tools and techniques.","Be prepared to discuss your understanding of cloud-native architectures."],"interviewFocus":["Adaptability to new technologies and problem-solving approaches.","Collaboration and communication skills in a remote or hybrid setting.","Understanding of distributed systems concepts relevant to cloud environments."],"commonQuestions":["Tell me about a challenging project you worked on.","How do you handle disagreements within a team?","Describe a time you had to learn a new technology quickly."]}}
- {"location":"On-site (e.g., San Francisco, Bellevue)","differences":{"tips":["Familiarize yourself with Databricks' products and use cases.","Practice coding problems that involve data manipulation and optimization.","Be ready to discuss your contributions to large-scale data projects."],"interviewFocus":["Deep understanding of core Databricks technologies and their applications.","Ability to apply theoretical knowledge to practical, real-world scenarios.","Problem-solving skills related to data processing and distributed computing."],"commonQuestions":["Describe your experience with our specific tech stack (e.g., Spark, Scala, Python).","How would you optimize a given SQL query for performance?","Walk me through a system you designed for scalability."]}}

## Round 1: Recruiter Screen
**Type:** HR Screening · **Difficulty:** Easy · **Duration:** 15 min
Initial screening call with HR to assess basic fit and motivation.
This initial screening call with a recruiter aims to understand your background, career aspirations, and motivation for applying to Databricks. They will also provide an overview of the company and the interview process. It's an opportunity to ask initial questions about the role and company culture.
**Interviewers look for:** Clear communication; Genuine interest in Databricks; Basic understanding of the software engineering field
**Evaluation criteria:** Basic communication skills; Understanding of the role and company; Enthusiasm and interest
**Common rejection reasons:** Inability to articulate thought process clearly.; Poor coding practices or syntax errors.; Fundamental misunderstanding of data structures or algorithms.; Inability to solve even basic coding problems.; Lack of enthusiasm or engagement.
## Questions

- Tell me about yourself and your background.
- Why are you interested in Databricks?
- What are you looking for in your next role?
- Do you have any questions for me?

## Preparation tips

- Be prepared to talk about your resume and why you are interested in Databricks.
- Research the company's mission, values, and recent achievements.
- Have a few questions ready to ask the recruiter about the role, team, or company.

## Round 2: Technical Coding Round 1
**Type:** Technical Phone Screen / Coding Interview · **Difficulty:** Medium · **Duration:** 45 min
Coding challenge focused on data structures and algorithms.
This round focuses on your core technical skills. You will be asked to solve one or two coding problems, typically involving data structures and algorithms. The interviewer will assess your ability to understand the problem, devise an efficient solution, write clean code, and analyze its time and space complexity. You'll likely code in a shared editor or on a whiteboard.
**Interviewers look for:** Logical thinking; Clean and efficient code; Understanding of fundamental CS concepts; Ability to communicate the solution approach
**Evaluation criteria:** Problem-solving ability; Coding proficiency; Data structure and algorithm knowledge; Ability to analyze complexity
**Common rejection reasons:** Inability to solve coding problems within the given time.; Incorrect or inefficient algorithms.; Poorly written or unreadable code.; Lack of understanding of time and space complexity.; Difficulty explaining the thought process.
## Questions

- Given an array of integers, find the contiguous subarray with the largest sum.
- Implement a function to reverse a linked list.
- Find the first non-repeating character in a string.
- Given two sorted arrays, find the median of the two sorted arrays.

## Preparation tips

- Practice coding problems on platforms like LeetCode, focusing on arrays, strings, linked lists, trees, and hash maps.
- Understand Big O notation and be able to analyze the complexity of your solutions.
- Practice explaining your thought process out loud as you solve problems.
- Ensure your code is well-structured, readable, and handles edge cases.

## Round 3: System Design Round
**Type:** System Design Interview · **Difficulty:** Medium · **Duration:** 60 min
Design a scalable system based on a given problem statement.
This round assesses your ability to design and scale software systems. You'll be given a high-level problem (e.g., design Twitter's feed, a URL shortener) and expected to discuss various components, data models, APIs, and trade-offs. The focus is on your thought process, ability to handle ambiguity, and understanding of distributed systems principles.
**Interviewers look for:** Ability to break down complex problems; Knowledge of common system components (databases, caches, load balancers); Sound reasoning for design choices; Consideration of failure modes and scalability
**Evaluation criteria:** System design thinking; Scalability and performance considerations; Trade-off analysis; Understanding of distributed systems; Problem decomposition
**Common rejection reasons:** Inability to design a scalable and robust system.; Lack of understanding of fundamental system design principles.; Poor trade-off analysis.; Difficulty in handling edge cases or failure scenarios.; Inability to communicate design choices effectively.
## Questions

- Design a URL shortening service like bit.ly.
- Design the Twitter feed.
- Design a rate limiter.
- How would you design a system to count unique visitors to a website?

## Preparation tips

- Study common system design concepts: load balancing, caching, databases (SQL vs. NoSQL), message queues, CDNs.
- Practice designing systems like Twitter, Uber, Netflix, etc.
- Understand trade-offs between different design choices.
- Be prepared to discuss scalability, availability, and fault tolerance.
- Think about data modeling and API design.

## Round 4: Hiring Manager Interview
**Type:** Behavioral / Hiring Manager Interview · **Difficulty:** Medium · **Duration:** 45 min
Behavioral questions to assess soft skills, teamwork, and cultural fit.
This interview focuses on your behavioral and soft skills. The hiring manager will ask questions about your past experiences to understand how you handle various situations, such as teamwork, conflict resolution, challenges, and successes. They will also assess your motivation, career goals, and how well you align with Databricks' culture.
**Interviewers look for:** Examples of past behavior that predict future performance.; Ability to work effectively in a team.; Resilience and ability to handle challenges.; Alignment with Databricks' culture and values.
**Evaluation criteria:** Teamwork and collaboration; Problem-solving approach; Adaptability and learning agility; Communication skills; Cultural fit
**Common rejection reasons:** Lack of alignment with company values.; Poor communication or interpersonal skills.; Inability to provide specific examples for behavioral questions.; Negative attitude or lack of enthusiasm.; Mismatch in career goals or expectations.
## Questions

- Tell me about a time you had a conflict with a teammate and how you resolved it.
- Describe a challenging project you worked on and what made it challenging.
- How do you prioritize your work when you have multiple competing deadlines?
- Tell me about a time you failed. What did you learn from it?
- What are your career goals for the next 3-5 years?

## Preparation tips

- Prepare specific examples using the STAR method (Situation, Task, Action, Result) for common behavioral questions.
- Reflect on your strengths, weaknesses, and career aspirations.
- Think about why you want to work at Databricks and what you can contribute.
- Be ready to discuss your resume and projects in detail.
- Prepare thoughtful questions for the hiring manager.