Databricks Software Engineer interview experience

The focus wasn’t on the model itself so much as the retrieval pipeline for an internal coding agent—specifically how that agent should find the most appropriate table or notebook to answer data-related questions.

We got into retrieval and re-ranking, and I talked through how I would index different assets and then score candidates. A big part of the conversation was handling noisy material, including notebooks or tables that might be irrelevant or unhelpful, and still producing something useful. We also talked about evaluation metrics—how I’d measure whether retrieval plus re-ranking was