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Databricks interview notes, page 1 of 22

Large Enterprises

Most of these Databricks write-ups come from Software Engineers (192), then Machine Learning Engineers (9) and Data Scientists (8). The most reported rounds are the technical phone screen (136), the system design round (57), the behavioral / leadership round (9) and the onsite coding round (6).

216 interview notes · updated Jul 2026

Databricks·Backend Engineer·Technical Phone Screen

May 2025
Phone screen for a backend role at Databricks, early May. One system design question, classic distributed systems territory. Pretty standard round, nothing unexpected.
  • Design a distributed file system.

“Classic problem that floats around on interview prep forums.”

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Databricks·Software Engineer·Technical Phone Screen

Apr 2026
Databricks SWE interview that went sideways despite solid prep. The candidate knew the material but got caught in a back-and-forth with the interviewer that ate up the clock, and never finished the implementation. Rejected.
  • Design a SnapshotSet iterator that supports versioned reads. Walk through your approach, discuss the tradeoffs between design options, and then implement it.

“I'd actually prepped this one, which made the rejection sting more.”

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Databricks·Software Engineer·Technical Phone Screen

Apr 2026
Databricks software engineer round focused on a generalized Tic-Tac-Toe design problem. Fairly implementation-heavy with a follow-up that pushed into async/API territory, which I did not fully anticipate.
  • Implement a generalized Tic-Tac-Toe game where the board dimensions and win condition (k-in-a-row) are configurable. Build a Game class with methods for making a move, checking for a win, and returning the current board state.
  • Follow-up: extend the game to support an AI player that picks its move by calling a provided random API to select a legal (unoccupied) cell.

“Spent way too long bikeshedding the constructor signature before writing any real code.”

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Databricks·Software Engineer·Recruiter / HR Screen

Apr 2026
Pretty standard recruiter screen for a software engineer role at Databricks. Mostly just talking through your background and why you want to make a move.
  • Walk me through your background and what you've been working on.
  • Why are you looking to make a move right now?
  • Why Databricks specifically, and why this role over competitors in the same space?

“Pretty much just a resume walkthrough.”

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Databricks·Machine Learning Engineer·Onsite - Behavioral / Leadership

Apr 2026
Behavioral round for an MLE role at Databricks, focused almost entirely on how you handle pushback and navigate technical disagreements. One question, but they really dug into it.
  • Tell me about a time you had a technical design disagreement with a teammate or another team. What were the competing positions, why did each side believe they were right, and how did you work through it? Walk me through the data, the alternatives you considered, the trade-offs, and what ultimately got decided. What would you do differently?

“This one went longer than I expected.”

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Databricks·Software Engineer·Technical Phone Screen

Apr 2026
Databricks SWE interview that leaned heavily on graph/tree problems. The core question was manageable but the follow-up pushed into 3D DP territory which is where things got uncomfortable for me.
  • Given a tree, compute some aggregate value per node from its subtree, then propagate information back up toward the root using a combination of BFS and tree DP.
  • Extend the tree DP solution to a 3D variant where each node's state includes an extra dimension such as remaining budget, parity, or k-th ancestor usage. Describe the recurrence and the complexity even if you don't write the full code.

“The two-pass structure tripped me up at first.”

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Databricks·Software Engineer·Technical Phone Screen

Apr 2026
Databricks SWE interview with a graph problem that looked straightforward until the follow-ups started piling up. The core question was manageable but they pushed hard on complexity, deduplication, and edge cases.
  • Given a city graph and multiple available commute modes (e.g., walking, biking, transit, driving), find the optimal route from a source to a destination across all modes.
  • What are the time and space complexities for the per-mode approach versus the combined multi-modal graph approach?
  • How would you deduplicate equivalent results in O(n) without sorting?
  • How do you handle edge cases like a mode being completely unreachable, equal-cost paths across different modes, or transfers between modes being prohibited?

“My first instinct was to throw everything into one big multi-modal graph and run Dijkstra once.”

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Databricks·Software Engineer·Onsite - System Design / Architecture

Apr 2026
Databricks system design round, and they went straight for a full chat server implementation. Not just high-level architecture either, they wanted to get into threading models, synchronization, scaling, the works. Left feeling like I'd only scratched the surface on a few of the deeper topics.
  • Design and implement a multi-threaded chat server that supports both 1:1 and group messaging, tracks online presence, and persists message history. Walk through your thread model choices, how you'd handle shared state, back-pressure, and scaling across multiple processes.

“This sprawled in a way I wasn't ready for.”

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Databricks·Software Engineer·Onsite - System Design / Architecture

Apr 2026
Databricks SWE interview with a system design question around building a document processing pipeline. Not a lot of context in what I have to share but it was a solid design problem that pushed me to think about scale and fault tolerance.
  • Design a document processing pipeline.

“This is the kind of question that feels straightforward until you start drawing boxes and realize you haven't thought about what happens when a document fails halfway through.”

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Databricks·Software Engineer·Technical Phone Screen

Apr 2026
Databricks coding round focused on a generalized tic-tac-toe problem. The DSU angle was the interesting part and I didn't see it coming at first.
  • Design and implement a generalized m×n board game where two players alternate placing marks, and after each move you need to efficiently check if the current player has formed a connected line of k marks in any direction (horizontal, vertical, or diagonal). Implement a move(row, col, player) method that returns whether the move results in a win.

“My first instinct was the naive scan approach, check all four directions from the placed cell and count.”

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