Databricks Coding & Algorithms interview questions focus on clean, scalable problem solving under realistic constraints. Expect interviews that often resemble LeetCode-style algorithm problems but with an emphasis on optimizations that matter at scale: time and space complexity, edge cases, and clear, maintainable code. Interviews typically use an online IDE for live coding and are woven into a loop that also assesses system design and collaboration. For candidates targeting data, platform, or ML infrastructure teams, concurrency, streaming, and data-structure tradeoffs commonly surface alongside pure algorithmic challenges. For effective interview preparation, prioritize deliberate practice of medium-to-hard algorithm problems, timed mock interviews, and explaining complexity tradeoffs aloud. Solidify one primary programming language so you can write correct, testable code quickly, and revisit concurrency primitives and common distributed-systems patterns if your role touches platform work. Practice communicating assumptions, iterating from a brute-force approach to optimized solutions, and writing concise test cases. This combination of technical depth, clear communication, and systems awareness is what Databricks typically evaluates.