Your question is Designing Databricks UX With Data. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Databricks is a leading data and AI platform used by enterprises to build data pipelines, run analytics, and develop machine learning and generative AI applications. Its products span technical surfaces like Databricks Workspace, Lakeflow, SQL Editor, AI/BI Dashboards, and Mosaic AI, serving both highly technical practitioners and less technical business users.
A design leader at Databricks wants to understand how you would shape product decisions in an environment where craft quality and measurable impact both matter. Internal feedback shows a recurring tension: some teams optimize heavily for usability metrics and experimentation, while others prioritize polished workflows and visual coherence but struggle to prove business impact. In recent usability studies, new users in Databricks Workspace reported that multi-step tasks such as creating a notebook, connecting to data, and sharing results feel powerful but cognitively heavy. At the same time, product leadership does not want design quality reduced to only click-throughs or task times.
Your challenge is to propose how you would approach designing a better end-to-end experience for one Databricks surface while balancing intuition, creativity, and analytical rigor.