Databricks·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Jun 2026

Summary

Databricks software engineer coding round. The problem itself was manageable but the interview dynamic felt off, like the interviewer was more interested in steering me toward their preferred solution than actually evaluating my thinking. Came out of it pretty frustrated.

Questions Asked (1)

Implement a snapshot set iterator where the return order of elements does not matter.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I came in with a design using a shared log list plus a dict and explained the tradeoff.

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AI HintsAI Generated

Suggested Approach

Clarify the requirements: snapshot semantics (elements present at iterator creation), order irrelevance, and expected operations (add, remove, iterate). Then design a data structure that supports efficient snapshot creation and iteration, likely using a persistent data structure or versioning, and discuss trade-offs between time and space.

Pro tip: Mention that snapshot isolation can be achieved with a persistent immutable data structure (e.g., a persistent hash set) or by copying on write, and highlight that order irrelevance allows using a hash-based structure for O(1) average operations.

1. Clarify Requirements

Ask about the expected operations (add, remove, iterate), concurrency needs, and whether the snapshot should reflect the set at the time of iterator creation. Confirm that order does not matter.

2. Choose Data Structure

Select a data structure that supports efficient snapshots. Consider persistent immutable sets (e.g., hash array mapped trie) or versioned sets with copy-on-write. Explain why order irrelevance simplifies the choice.

3. Design Snapshot Mechanism

Describe how to create a snapshot: either by capturing a reference to the current version (persistent) or by copying the current state (copy-on-write). Discuss trade-offs in time and space.

4. Implement Iterator

Implement the iterator to traverse the snapshot. Since order doesn't matter, any traversal order is acceptable. Ensure the iterator is independent of subsequent modifications to the original set.

5. Analyze Trade-offs

Compare approaches: persistent data structures offer O(1) snapshot creation but may have higher constant factors; copying gives O(n) snapshot but simpler implementation. Discuss memory overhead and concurrency implications.

Key Points to Mention

Snapshot isolation: iterator sees a consistent view of the set at creation time.
Order irrelevance allows using hash-based structures for O(1) average add/remove/contains.
Persistent data structures (e.g., HAMT) provide efficient snapshots with structural sharing.
Copy-on-write or full copy alternatives and their time/space trade-offs.
Concurrency considerations: thread-safe snapshots without locking the entire set.
Iterator implementation details: fail-fast vs. snapshot semantics.

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