Design for Databricks SQL Analysts | Dataford Interview Questions

Company Context

Databricks is a leading data and AI platform used by enterprises to unify data engineering, analytics, and machine learning on the Lakehouse. One of its core surfaces, Databricks SQL, serves analysts, data scientists, and business users who need to explore data, write queries, and build dashboards quickly.

Problem

Databricks wants to improve the UX of Databricks SQL Editor and dashboard workflows for less technical analytics users. Internal feedback shows that new and intermediate users often struggle to move from a business question to a working query and shareable insight. In usability sessions, users report friction around understanding schema context, recovering from SQL errors, and knowing what to do next after opening the editor. Product telemetry shows that 38% of new Databricks SQL users run only 0-1 successful queries in their first week, and only 24% publish a dashboard within 30 days.

Your task is not to redesign the full product. Instead, focus on identifying who you are designing for, what their primary goals and pain points are, and how that should shape the first set of UX/UI improvements.

Deliverables

Define the most important user segments for this problem within Databricks SQL.
Identify the primary goals, jobs-to-be-done, and pain points for your target segment(s).
Prioritize the top UX/UI opportunities you would address first, and explain what you would not prioritize yet.
Describe the product vision for a better Databricks SQL authoring experience for the chosen users.
Define how you would measure whether your proposed improvements are successful.

Constraints

You can only scope an MVP that a small cross-functional team can ship in one quarter.
You should focus on existing Databricks surfaces, especially Databricks SQL Editor, query results, and dashboard creation flows.
Assume no major backend re-architecture or new AI platform investment beyond lightweight assistive features.
Solutions must work for enterprise environments with governance, permissions, and auditability requirements.

Problem

Company Context

Problem

Deliverables

Define the most important user segments for this problem within Databricks SQL.
Identify the primary goals, jobs-to-be-done, and pain points for your target segment(s).
Prioritize the top UX/UI opportunities you would address first, and explain what you would not prioritize yet.
Describe the product vision for a better Databricks SQL authoring experience for the chosen users.
Define how you would measure whether your proposed improvements are successful.

Constraints

You can only scope an MVP that a small cross-functional team can ship in one quarter.
You should focus on existing Databricks surfaces, especially Databricks SQL Editor, query results, and dashboard creation flows.
Assume no major backend re-architecture or new AI platform investment beyond lightweight assistive features.
Solutions must work for enterprise environments with governance, permissions, and auditability requirements.

Problem

Company Context

Problem

Deliverables

Define the most important user segments for this problem within Databricks SQL.
Identify the primary goals, jobs-to-be-done, and pain points for your target segment(s).
Prioritize the top UX/UI opportunities you would address first, and explain what you would not prioritize yet.
Describe the product vision for a better Databricks SQL authoring experience for the chosen users.
Define how you would measure whether your proposed improvements are successful.

Constraints

You can only scope an MVP that a small cross-functional team can ship in one quarter.
You should focus on existing Databricks surfaces, especially Databricks SQL Editor, query results, and dashboard creation flows.
Assume no major backend re-architecture or new AI platform investment beyond lightweight assistive features.
Solutions must work for enterprise environments with governance, permissions, and auditability requirements.

Problem

Company Context

Problem

Deliverables

Define the most important user segments for this problem within Databricks SQL.
Identify the primary goals, jobs-to-be-done, and pain points for your target segment(s).
Prioritize the top UX/UI opportunities you would address first, and explain what you would not prioritize yet.
Describe the product vision for a better Databricks SQL authoring experience for the chosen users.
Define how you would measure whether your proposed improvements are successful.

Constraints

You can only scope an MVP that a small cross-functional team can ship in one quarter.
You should focus on existing Databricks surfaces, especially Databricks SQL Editor, query results, and dashboard creation flows.
Assume no major backend re-architecture or new AI platform investment beyond lightweight assistive features.
Solutions must work for enterprise environments with governance, permissions, and auditability requirements.