Databricks·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

May 2026

Summary

Databricks SWE interview with a graph traversal problem that looked like a shortest path question but had a lexicographic twist that tripped me up for a bit. Solid problem, not your average Dijkstra warmup.

Questions Asked (1)

Given an m x n grid with a start and destination cell, where each cell holds a value indicating a transport mode (or is blocked), and separate matrices for time and cost to enter each cell, find a path from start to destination using exactly one transport mode that minimizes (total_time, total_cost) lexicographically. Return -1 if unreachable.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

My first instinct was just Dijkstra with (time, cost) as a tuple key and I went with that.

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AI HintsAI Generated

Suggested Approach

Model the grid as a graph where each cell is a node, and edges represent moves to adjacent cells with weights (time, cost) from the destination cell's matrices. Since the path must use exactly one transport mode, run a separate shortest path search for each mode, considering only cells with that mode (plus start and destination), and then select the lexicographically smallest (time, cost) among the results. Use Dijkstra's algorithm with lexicographic comparison for each mode.

Pro tip: Clarify upfront whether start and destination cells have transport modes and whether they must match the chosen mode; this ambiguity can drastically change the solution and shows attention to detail.

1. Clarify problem constraints and assumptions

Ask about blocked cells, whether start/destination have modes, if movement is 4-directional, and if time/cost are non-negative. Confirm that 'exactly one transport mode' means all intermediate cells must have the same mode.

2. Model as a graph and define edge weights

Treat each cell as a node. For a move from cell A to adjacent cell B, the edge weight is (time[B], cost[B]) from the given matrices. Blocked cells are excluded.

3. Run Dijkstra per transport mode

For each distinct transport mode, run Dijkstra from start to destination, allowing only cells with that mode (and possibly start/destination). Use lexicographic comparison of (time, cost) to select the best path.

4. Compare results and return optimal

Among all modes that yield a valid path, pick the one with lexicographically smallest (total_time, total_cost). If none, return -1.

5. Analyze complexity and discuss optimizations

Time complexity is O(M * (mn log(mn))) where M is number of modes. Mention potential optimizations like early termination or multi-source Dijkstra if modes are many.

Key Points to Mention

Lexicographic comparison of (time, cost) tuples in priority queue
Dijkstra's algorithm with non-negative weights
Handling of blocked cells and mode restrictions
Separate search per transport mode to enforce exactly one mode
Time and space complexity analysis
Edge cases: start equals destination, unreachable, multiple modes with same optimal cost

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.