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Databricks·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Databricks SWE interview with a graph traversal problem I'd seen referenced on forums before. Nothing too wild, but the multi-mode constraint adds a layer that trips you up if you try to be clever about it.

Questions Asked (1)

Q1

Given a 2D grid with a start and destination cell, four movement modes each allow traversal through different sets of cells. Each mode has a fixed per-step time and cost. Find the mode that minimizes total travel time; break ties by minimum cost.

Algorithms & Data Structures
Author's notes

My first instinct was to try some unified search that mixed modes, which would've been a mess.

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AI HintsAI Generated

Suggested Approach

Model the problem as a graph where each cell is a node, and edges represent moves within the same mode with weights (time, cost). For each mode, run a shortest path algorithm (e.g., Dijkstra) to find the optimal (time, cost) to the destination, then compare across modes using lexicographic ordering (time first, then cost).

Pro tip: Clarify whether switching modes mid-path is allowed; if not, treat each mode independently. Also, consider using a modified Dijkstra that tracks both time and cost to handle ties efficiently.

1. Clarify problem constraints

Ask if mode switching is allowed, if movement costs are uniform, and if the grid has obstacles. This determines if we need a multi-layer graph or separate runs per mode.

2. Model as a graph

Create a graph where nodes are cells and edges represent valid moves for a given mode. Each edge has a weight tuple (time, cost).

3. Compute shortest paths per mode

For each mode, run Dijkstra's algorithm to find the path minimizing time, breaking ties by cost. Use a priority queue ordered lexicographically by (time, cost).

4. Compare results and select optimal mode

Compare the (time, cost) pairs from each mode. Choose the mode with the smallest time; if tied, choose the one with the smallest cost.

5. Analyze complexity and optimize

Discuss time complexity (O(M * (V log V + E)) for M modes) and potential optimizations like early termination or bidirectional search.

Key Points to Mention

  • Graph representation: cells as nodes, moves as edges with (time, cost) weights.
  • Dijkstra's algorithm with lexicographic priority queue for (time, cost).
  • Handling multiple modes: either separate runs or a multi-layer graph if switching allowed.
  • Tie-breaking: compare time first, then cost.
  • Time complexity: O(M * (V log V + E)) where M is number of modes.
  • Edge cases: unreachable destination, start equals destination, negative weights (not applicable).

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