Databricks·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026

Summary

Databricks SWE interview with a file encryption optimization problem that looks straightforward until you actually think about the cost model. The batch API wrapping subdirectories changes everything.

Questions Asked (1)

You have a root directory with files and nested subdirectories. Some files are already encrypted, some aren't. You have two APIs: one encrypts a single file with a fixed request overhead plus a per-file cost, and another batch-encrypts all unencrypted files in a given directory and all its subdirectories, also with a fixed overhead but only one per-file cost multiplied by the count. Find the minimum total time to encrypt all unencrypted files.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The part that tripped me up was figuring out when it's actually cheaper to call the directory API versus just looping individual files.

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AI HintsAI Generated

Suggested Approach

Model the problem as a tree where each node represents a directory, and decide for each subtree whether to use batch encryption or individual file encryption. Use dynamic programming to compute the minimum cost for each subtree, considering the trade-off between fixed overheads and per-file costs.

Pro tip: Clarify the cost parameters and constraints upfront, and discuss how your solution scales with the number of files and directories, as Databricks values efficient algorithms for large-scale data.

1. Understand the problem and define costs

Restate the problem to ensure clarity: identify the fixed overhead and per-file cost for both APIs, and note that batch encryption applies to all unencrypted files in a directory and its subdirectories.

2. Model as a tree and define DP state

Represent the directory structure as a tree. For each node, define DP states: the minimum cost to encrypt all unencrypted files in its subtree, possibly considering whether the node is covered by a batch operation from an ancestor.

3. Derive recurrence relations

For each node, compute the cost if we use batch encryption at this node (covering the entire subtree) versus encrypting files individually or using batch operations in child subtrees. Combine child costs appropriately.

4. Implement and optimize

Implement the DP using post-order traversal. Optimize by noting that batch encryption at a node may make child batch operations redundant, and handle already encrypted files by excluding them from counts.

5. Analyze complexity and edge cases

Discuss time and space complexity (O(N) where N is number of files/directories). Consider edge cases: empty directories, all files encrypted, deep nesting, and large numbers of files.

Key Points to Mention

Dynamic programming on trees with states representing whether a batch operation covers the subtree.
Trade-off between fixed overhead and per-file cost: batch is beneficial when many unencrypted files exist in a subtree.
Handling already encrypted files: they should be ignored in counts and costs.
Post-order traversal to compute subtree costs bottom-up.
Complexity analysis: O(N) time and O(H) space for recursion stack, where H is tree height.
Potential optimization: prune subtrees with no unencrypted files.

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