Scale Engineer

Software Engineer

Software EngineerL4Medium to Hard

The Databricks Software Engineer L4 interview process is designed to assess a candidate's technical proficiency, problem-solving abilities, and cultural fit for the company. It typically involves multiple rounds, including technical interviews focusing on data structures, algorithms, and system design, as well as behavioral interviews to gauge collaboration and communication skills.

Rounds·4

Timeline·~14d

Experience·3 - 7 yrs

Comp band·US$130000 - US$180000

Interview time·195 min

Evaluation

What they measure.

  • Problem-solving skills
  • Algorithmic thinking
  • Data structure knowledge
  • Coding proficiency (clarity, efficiency, correctness)
  • System design capabilities (scalability, reliability, maintainability)
  • Communication skills
  • Collaboration and teamwork
  • Cultural fit and alignment with Databricks values

Preparation

How to prepare.

Tips

  1. Review fundamental data structures (arrays, linked lists, trees, graphs, hash tables) and algorithms (sorting, searching, dynamic programming, graph traversal).
  2. Practice coding problems on platforms like LeetCode, HackerRank, or AlgoExpert, focusing on medium to hard difficulty.
  3. Study system design principles, including scalability, availability, consistency, and common design patterns (e.g., load balancing, caching, message queues, databases).
  4. Prepare for behavioral questions by reflecting on your past experiences using the STAR method (Situation, Task, Action, Result).
  5. Understand Databricks' core products and technologies (e.g., Apache Spark, Delta Lake, Unity Catalog) and how they are used.
  6. Research common interview questions for Software Engineer roles at Databricks and similar companies.
  7. Practice explaining your thought process clearly and concisely, both for coding and system design problems.
  8. Prepare questions to ask the interviewer about the role, team, and company culture.

Study plan

Fig · Study plan — 04 phases

01 / 04
01

Phase 01 of 04

Data Structures and Algorithms

Weeks 1-2: Data Structures & Algorithms fundamentals. Solve 35-40 problems.

Weeks 1-2: Focus on core data structures and algorithms. Cover arrays, linked lists, stacks, queues, trees (binary, BST, AVL), heaps, hash tables, graphs. Practice algorithms like sorting (quicksort, mergesort), searching (binary search), recursion, dynamic programming, and graph traversal (BFS, DFS). Aim to solve 5-7 problems per day.

Questions

Commonly asked.

  • Given an array of integers, find the contiguous subarray with the largest sum.
  • Design a system to count unique visitors to a website in real-time.
  • Explain the difference between a process and a thread.
  • How would you design a rate limiter?
  • Describe a time you had to mentor a junior engineer.
  • What are the trade-offs between using a relational database and a NoSQL database for a large-scale application?
  • Implement a function to reverse a linked list.
  • Tell me about a challenging project you worked on and how you overcame obstacles.
  • How would you design a distributed key-value store?
  • What is the time and space complexity of your solution?

Locations

Regional differences.

Fig · Regions — 03 locations

01 / 03

Location

USA

Interview focus

System Design: Emphasis on scalability, reliability, and distributed systems.Problem-Solving: Ability to break down complex problems and articulate solutions.Coding Proficiency: Clean, efficient, and well-tested code.Collaboration: Teamwork and communication skills.

Common questions

  • Discuss a challenging technical problem you solved at your previous company.
  • How would you design a distributed caching system?
  • Explain the trade-offs between different database types.
  • Describe a time you had to deal with a difficult stakeholder.

Tips

  • For US-based interviews, be prepared for in-depth system design questions and coding challenges.
  • For international locations, while technical rigor is maintained, there might be a slightly higher emphasis on foundational computer science concepts and clear communication.
  • Research Databricks' specific products and technologies relevant to the role and location.

Rounds

Round-by-round.

Expand a step for evaluation criteria, sample questions, and prep notes.

DSA

Coding questions at Databricks.

Frequently reported on Databricks loops

View all at Databricks

Other guides

More at Databricks.