Databricks Interview Questions


     Databricks Interview Questions

Here’s a comprehensive guide to Databricks interview questions, categorized by category and experience level.

Key Concepts & Architecture

  • What is Databricks?  Explain its primary purpose and how it sits within the extensive data landscape.
  • Describe the core components of the Databricks architecture. (Workspaces, clusters, notebooks, jobs, Databricks File System (DBFS), etc.)
  • What is a Databricks cluster? Differentiate between standard, job, and all-purpose clusters.
  • Explain Delta Lake. What advantages does it bring over traditional data lake formats?
  • How do you implement Databricks clusters for cost optimization? (Cluster sizing, auto-scaling, spot instances)

Spark Fundamentals

  • What are RDDs? How do they underpin distributed computing in Spark?
  • Explain the difference between transformations and actions in Spark.
  • Describe common Spark transformations (map, filter, reduceByKey, join, etc.) and provide use cases.
  • Describe everyday Spark actions (collect, count, take, foreach, etc.) and when to use them.
  • How do you optimize Spark jobs? Discuss techniques like partitioning, caching, and avoiding shuffles.

Data Engineering

  • How do you ingest data from various sources (databases, cloud storage, streaming) into Databricks?
  • Describe a typical ETL process within Databricks. What tools and operations do you use?
  • Explain the data quality checks you implement in Databricks pipelines.
  • How do you schedule and orchestrate Databricks jobs?
  • Discuss strategies for monitoring Databricks jobs and troubleshooting issues.

Data Analysis & ML

  • What are the different libraries available for data exploration and visualization within Databricks?
  • How do you use Databricks notebooks for exploratory data analysis (EDA)?
  • Describe the process of feature engineering in Databricks.
  • Explain MLflow. How do you use it for model tracking and deployment?
  • How do you perform hyperparameter tuning in a Databricks environment?

Experience-Based Questions


  • Describe a data-related project you’ve worked on. How did you use Spark or similar tools?
  • Given a scenario, how would you design a primary ETL pipeline in Databricks?
  • Explain the different file formats supported in Databricks (CSV, Parquet, JSON, etc.) and when to use each one.


  • Discuss performance optimization challenges you’ve faced in large-scale Databricks implementations and how you addressed them.
  • How have you handled data security and governance in Databricks, especially in sensitive environments?
  • Describe how you collaborate with other teams (data scientists, analysts) on Databricks projects.
  • How do you integrate Databricks with other cloud services (e.g., Azure Blob Storage, AWS S3)?

Tips for Answering Databricks Interview Questions

  • Show real-world understanding: Don’t just memorize definitions; demonstrate how you’ve applied Databricks concepts in projects.
  • Tailor your answers:  Focus on the skills relevant to the job description and the company’s specific use cases.
  • Explain your thought process: Walk through your reasoning behind design choices and problem-solving approaches.
  • Be prepared to code: Some interviews may involve live coding challenges or whiteboarding exercises.

Databricks Training Demo Day 1 Video:

You can find more information about Databricks Training in this Dtabricks Docs Link



Unogeeks is the No.1 IT Training Institute for Databricks Training. Anyone Disagree? Please drop in a comment

You can check out our other latest blogs on Databricks Training here – Databricks Blogs

Please check out our Best In Class Databricks Training Details here – Databricks Training

 Follow & Connect with us:


For Training inquiries:

Call/Whatsapp: +91 73960 33555

Mail us at:

Our Website ➜

Follow us:





Leave a Reply

Your email address will not be published. Required fields are marked *