Top 21
Prep plan
Updated weekly · Last refresh Oct 17

Databricks Data Analyst Interview Questions

The questions to prepare for a Databricks Data Analyst interview. Questions from real interview reports rank first. Updated daily.

21questions
~3htotal time
Track your progressSign up free to work through all 21 questions and resume where you left off.
Start practicing free →
1
SQL & Data ManipulationStart here. 3 questions · ~29 min
Clean Event Statuses for AnalysisEasy
Practice

Clean raw status text with TRIM and LOWER, filter unusable rows, and count usable events by cleaned status.

Data WranglingETLQualityDatabricks
SQL Query OptimizationMedium
Practice

Optimize a slow PostgreSQL query that aggregates completed transactions while preserving customers with no matching activity.

Performance Tuningdatabase optimizationindexesDatabricks
Write a Basic SQL ExtractionEasy
Practice

Extract completed orders above a specified amount and return them in descending amount order.

JoinsData ManipulationData WranglingDatabricks
2
Pipelines7 questions · ~68 min
Data Frames in Python PipelinesEasy

Explain what Python data frames are and where they fit in ETL and analytics workflows.

ETLData ModelingQualityDatabricks
Sort Data in a PipelineEasy

Implement a basic sorting step as part of a simple data pipeline workflow.

Data WranglingETLQualityDatabricks
Average Calculation in a PipelineEasy

Implement a simple Python transformation that computes the average of a numeric list.

Data WranglingETLQualityDatabricks
More Pipelines questions with a free account

Sign up to see every question

Create a free account to unlock this list and practice real interview questions.

Get my prep plan
3
Behavioral & Leadership9 questions · ~87 min
More Behavioral & Leadership questions with a free account
4
More topics2 questions · ~19 min
Analyze a Successful CampaignEasy

Describe how you would evaluate a successful marketing campaign using funnel KPIs, conversion, and ROI.

KPIsDiagnosisEngagement MetricsDatabricks
Finding Trends and PatternsMedium

Explain how to detect meaningful trends and patterns in a dataset using time comparisons, segmentation, and validation.

analyticsLagging Indicatorsdata pointsDatabricks
The finish line: interview-readyComplete all 21 questions to finish this plan.