Databricks Software Engineer Interview Questions
& Process

there were 2 stages: coding and algorithms. in the coding stage i had to write methods and tests for a LazyArray, and in the algorithms stage there was a problem where i had to use set (i was writing in c++) but the interviewer asked me how else could i implement the code with all possble data structres, array, heap etc and analyse runtime of these alternative solutions

The Databricks interview process typically takes about two to eight weeks and kicks off with a recruiter screen where I go over my background, experience, and why I’m interested in the company. After that, there’s a technical phone screen where I solve algorithm or coding questions live, usually using CoderPad. If that goes well, I move on to a virtual onsite with three to five rounds covering coding, system design, and behavioral topics. For software engineering positions, the interviews go deep into data structures, algorithms, and scalable system design, while data or ML roles also cover Spark, data pipelines, and machine learning case studies. The interviews are challenging but fair, often ramping up in difficulty to evaluate my reasoning, problem-solving depth, and clarity in communication. Afterward, a hiring committee reviews all the feedback to decide whether to make an offer, and sometimes there’s a team-matching step. Overall, the process is thorough and focuses on clarity, correctness, and thoughtful engineering tradeoffs.

I went through the early stages of the Databricks interview process and found the overall experience pretty underwhelming. The first interview was a conversation with a recruiter. Although they were friendly, I felt like they weren’t very familiar with the company’s technical work or core products. It was hard to get clear answers to basic questions about what the company actually does. This was frustrating, especially since recruiters are the first gatekeepers in the process. The second interview was a technical one. The interviewer was polite but came across as disengaged and rushed. There was almost no introduction or small talk before jumping straight into coding. The question was a standard algorithmic problem (similar to "438. Find All Anagrams in a String" on LeetCode). The difficulty was fair, but the communication style made the interview feel uncomfortable. I was told to analyze time complexity before even writing the code, which felt a bit premature for a graduate-level interview. Overall, the process felt kind of impersonal and inconsistent in quality. I left feeling that some interviewers weren’t fully invested in giving candidates a positive experience. Databricks is clearly a strong company, but I hope they improve the consistency and clarity of their early-stage interviews.