← Databricks Interview Insights

Databricks·Software Engineer·Technical Phone Screen·Intermediate

IntermediateRejected
Apr 2026

Summary

Interviewed for a Software Engineer role at Databricks and got burned by going in with assumptions. One coding question, one rejection.

Questions Asked (1)

Q1

Implement a snapshot iterator. The iterator does not need to preserve the original insertion order of elements.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

I'd seen this question before and immediately locked in on order-preservation because every writeup I'd read made that sound like a hard requirement.

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AI HintsAI Generated

Suggested Approach

Clarify the requirements: snapshot semantics, iterator behavior, and thread-safety. Then design a data structure that supports efficient snapshot creation and iteration, such as a persistent data structure or copy-on-write. Discuss trade-offs between memory, time, and concurrency, and implement a simple version.

Pro tip: Mention that the iterator should be fail-safe (not throw ConcurrentModificationException) and that snapshot isolation can be achieved with immutable data structures or versioning. Also, consider the memory overhead of snapshots and how to handle large datasets.

1. Clarify requirements

Ask about expected operations (add, remove, iterate), concurrency needs, and whether the snapshot should be a point-in-time view. Confirm that order doesn't matter, so we can use unordered structures.

2. Choose a snapshot strategy

Decide between copying the entire collection, using a persistent data structure (e.g., immutable linked list or tree), or copy-on-write. Consider memory and time trade-offs.

3. Design the iterator

Implement an iterator that traverses the snapshot without being affected by subsequent modifications. Ensure it supports standard operations like hasNext() and next().

4. Handle concurrency (if needed)

If thread-safety is required, use synchronization or lock-free techniques. Discuss how snapshots provide a consistent view without blocking writers.

5. Analyze trade-offs

Compare approaches: full copy is simple but memory-heavy; persistent structures share memory but may have overhead; copy-on-write is efficient for read-heavy workloads. Mention garbage collection implications.

Key Points to Mention

  • Snapshot isolation: iterator sees a consistent view of the collection at the time of creation.
  • Data structures: persistent/immutable data structures (e.g., linked list, balanced tree) or copy-on-write arrays.
  • Concurrency: fail-safe iteration, no ConcurrentModificationException, and thread-safety considerations.
  • Memory overhead: snapshots can increase memory usage; discuss sharing vs copying.
  • Time complexity: O(1) snapshot creation vs O(n) copy; iteration O(n).
  • Use cases: Databricks likely deals with large-scale data, so efficiency and scalability matter.

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