Azure Databricks interviews typically assess your knowledge and experience with big data processing, Apache Spark, cloud computing, and data engineering principles. They may cover a wide range of topics, from basic concepts to advanced scenarios.

Types of questions you might encounter:

• Conceptual questions:
  • What is Azure Databricks, and why is it used?
  • Explain the architecture of Azure Databricks.
  • What are the different types of clusters available in Azure Databricks?
  • What is a notebook in Databricks, and how is it used?
  • How does Databricks integrate with other Azure services?
• Technical questions:
  • How do you read data from various sources into Databricks?
  • Explain Spark transformations and actions with examples.
  • How do you optimize Spark jobs for performance?
  • What are Delta tables, and what are their advantages?
  • How do you schedule and automate jobs in Databricks?
• Scenario-based questions:
  • Design a solution for real-time data processing using Databricks.
  • How would you troubleshoot a failing Spark job?
  • Explain your experience with Databricks in a previous project.

How to prepare:

1. Review the basics: Make sure you have a solid understanding of Apache Spark, big data concepts, and cloud computing fundamentals.
2. Familiarize yourself with Azure Databricks: Understand its architecture, components, and features. Go through the documentation and tutorials provided by Microsoft.
3. Practice Spark: Work on Spark projects using Python or Scala. Try out different transformations, actions, and data processing techniques.
4. Explore Databricks notebooks: Create and run notebooks in Databricks to get hands-on experience. Experiment with different data sources and scenarios.