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Updated weekly · Last refresh Sep 24

Databricks Software Engineer Interview Questions

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

50questions
~8htotal time
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1
CodingStart here. 18 questions · ~175 min
Implement and Debug a ClassHard
Practice

Build a deterministic DAG scheduler that detects cycles and computes each task's earliest finish time and overall critical-path duration.

DebuggingDatabricks
Bus Waiting Time CalculationEasy
Practice

Compute the wait for Databricks shuttle service using modular arithmetic on minutes since midnight.

Databricks
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2
System Design17 questions · ~165 min
Construct an API for a Practical ProblemHard

Design a production-ready ML API by clarifying the task, defining its contract, and planning serving, evaluation, and failure handling.

api designml inferenceapi gatewayDatabricks
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3
Pipelines4 questions · ~39 min
Freeze Version Set and IterateHard

Implement a reproducible Databricks pipeline that freezes input versions before deterministic iteration.

data pipelinesiterationIdempotencyDatabricks
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4
Execution3 questions · ~29 min
Break Down Large TasksHard

Explain how to decompose ambiguous engineering work into milestones, dependencies, estimates, and actionable tasks.

Backlog Managementcritical pathProject ManagementDatabricks
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5
Behavioral & Leadership5 questions · ~49 min
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6
More topics3 questions · ~29 min
SQL Trigger to Update Related FieldsMedium

Tests your ability to design correct data updates and handle relational dependencies in triggers.

Databricks
IP Address Coding ProblemMedium

Assesses your ability to implement correct logic for networking-related coding problems.

Databricks
Break Down a Multi-Month ProjectMedium

Tests your ability to translate long-term ambiguity into actionable technical plans.

Project ManagementDatabricks
Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
Eventual ConsistencyMedium
Practice
Practice drill

Find catalog items that were updated in the source but not yet reflected in Spotify's serving layer.

data consistencySpotifyDatabricks
Window Functions for AnalyticsHard
Practice
Practice drill

Calculate entity-level running totals and three-row moving averages over a date-filtered partitioned fact table.

Window Functionslarge datasetsdata managementDatabricks
Clean Event Statuses for AnalysisEasy
Practice
Practice drill

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

Data WranglingETLQualityDatabricks
The finish line: interview-readyComplete all 50 questions plus 3 hands-on drills to finish this plan.