9 Azure Databricks Interview Questions (With Sample Answers)

Updated 18 March 2023

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Interviews provide you with the opportunity to demonstrate your skills and qualifications for the role. In the Azure Databricks interview, you can expect questions about the fundamentals of a cloud server and Databricks features and integration with other technologies. If you are familiar with potential interview questions, you may find it easier to advance in the hiring process. In this article, we discuss nine Azure Databricks interview questions with sample answers and review a few interview tips to help you prepare for your next interview.

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9 Azure Databricks Interview Questions And Answers

Consider the following nine Azure Databricks interview questions to prepare for an interview:

1. What is Azure Databricks?

This interview question helps the interviewer gauge a candidate's understanding of the fundamentals. While answering, be concise and highlight the key features of the Databricks you find most important.

Sample answer: 'Azure Databricks is a robust platform for large data analytics built on Apache Spark. It is simple to use and one can quickly install it on the Azure server. Data engineers who wish to work with big data hosted in the cloud often use Databricks because of its excellent integration with the other Azure services.'

2. What is the use of auto-scaling in Azure Databricks?

Auto-scaling allows the program to run effectively even under high load. Such a question helps the hiring manager assess your knowledge of auto-scaling in Azure. While answering, briefly define Databricks's auto-scaling feature and mention its key benefit.

Sample answer: 'The auto-scaling functionality of Databricks enables users to automatically scale the cluster up or down with their demands. Ensuring users are only using the resources they require helps save time and money.'

3. What are the major benefits of Azure Databricks?

Azure Databricks is a market-leading, cloud-based data management tool helpful for processing and manipulating enormous amounts of data and analysing the data using machine learning models. A recruiter may ask such questions to find your interest in Databricks. To convince the interviewer of your technical proficiency, mention a few key benefits and their importance in your answer.

Sample answer: 'Though Azure Databricks is based on Spark, it supports many other programming languages such as Python, R and SQL. To integrate these with Spark, Databricks converted these languages on the backend through application performance indicators (APIs). This eliminates the users' requirement to learn any additional programming language for distributed analytics. Azure Databricks is highly adaptable and simple to implement, making distributed analytics much easier to use.

Databricks offers an integrated workspace that supports collaboration through a multi-user environment, enabling a team to develop innovative machine learning and streaming applications on Spark. It also provides monitoring and recovery tools that help recover clusters from failures without manual intervention. With Databricks, we can make our cloud infrastructures secure and fast without major customisation with Spark.'

4. What are the different kinds of clusters in Azure Databricks and what are the functions of each?

Asking such questions helps the interviewer test your theoretical knowledge by observing how well you understand the concepts. It is crucial that you mention all four main types and briefly describe each in your response to this question.

Sample answer: 'Azure Databricks has four cluster types. Interactive, job, low-priority and high-priority. Interactive clusters help with data exploration and ad hoc queries. These clusters provide low latency and high concurrency. We utilise job clusters for batch job execution. We can automatically scale job clusters to match the requirements. Low-priority clusters are less expensive than other cluster types but offer low performance. These clusters are suitable for tasks, such as development and testing, that may require lesser performance. High-priority clusters are more costly than other clusters, but they provide the best performance. These clusters are suitable for production-level workloads.'

5. What is the use of Kafka in Azure Databricks?

Apache Kafka is a decentralised streaming platform for constructing real-time streaming data pipelines and stream-adaptive applications. Such questions allow you to demonstrate your understanding of other tools and integrations with Databricks. In your response, mention how Kafka improves the workflow when integrating it with Azure Databricks.

Sample answer: 'Azure Databricks uses Kafka for streaming data. It can help collect data from many sources, such as sensors, logs and financial transactions. Kafka is also capable of real-time processing and analysis of streaming data.'

6. How do you manage the Databricks code while working with a team using the team foundation server (TFS) or Git?

Both TFS and Git allow easy code management through effective collaboration among teams and by utilising version control. Such questions help the hiring manager assess your capacity to manage the code base of a project effectively and also assess if you have experience in coding with Databricks. In your answer, mention the key features of both TFS and Git and briefly explain the major steps you take to manage the Databricks code.

Sample answer: "TFS is a Microsoft solution that supports over five million lines of code, whereas Git is open-source and supports approximately 15 million lines of code. Git is less secure as we can not assign read and write permission, but with TFS, we can assign such granular permissions.

Azure Databricks allows easy notebook integration with Git, Bitbucket cloud and TFS. The integrating process differs slightly depending on the service we integrate. After the integration, Databricks code functions similar to a project clone. To effectively manage the Databricks code, I start by creating a notebook, committing it to the version control system and then updating it."

7. Can you run Databricks on private cloud infrastructure?

Such a question may help the interviewer assess your knowledge about the versatility of Databricks. You can also use this question to demonstrate your problem-solving and attention to detail capabilities. In your answer, mention the available cloud server options and also briefly explain how to run it on a private cloud.

Sample answer: 'Amazon Web Services (AWS) and Azure are the only options available now. Databricks utilises open-source Spark. We can develop our own cluster and run it in a private cloud, but in that case, we miss out on Databricks' full administration capabilities and features.'

8. What major challenges did you face in your last role?

The answer to such a question entirely depends on your prior professional experience. The hiring manager is often interested in knowing the problems you faced and your technique for overcoming them. If you have worked with Azure Databricks in your past role, you may mention related challenges or any data or server management-related challenges that hindered efficient workflow.

Sample answer: "In my last role as a data engineer, I faced many challenges, primarily because it was my first job. One of the key challenges was to clean up the gathered data. Though I struggled at first for a few weeks, I soon learned and developed some algorithms to do the 80-90% data clean job automatically.

Another major challenge was the loss of productivity because of inefficiency in team collaboration. The organisation used to store data on multiple servers and the team used to take the data offline for processing. This resulted in many errors and much slower data-driven actions. Though it took me almost two months, I helped unify all the data collection on a single Azure server and implemented Databricks, which automated most of the process and helped gain insights in real-time."

9. What do you understand by mapping data flows?

Such a technical question helps the interviewer to assess your domain knowledge. You can use this question to show your familiarity with the working concepts of Databricks. In your response, briefly explain what mapping data flow does and how it helps with the workflow.

Sample answer: 'Microsoft offers mapping data flows which do not require coding for a simpler data integration experience, as opposed to data factory pipelines. It is a graphical method for designing data transformation pipelines. It helps transform the data flow into Azure data factory (ADF) activities and execute as part of ADF pipelines.'

Tips To Prepare For Your Azure Databricks Interview Questions

Here are a few useful tips to improve your chances of success in an Azure Databricks interview:

Develop your skills

Before applying for a Databricks role, it is helpful to develop the key skills for the job, including competency in cloud server management and data engineering. One of the effective ways to accomplish this is to pursue related online courses and develop test projects that can help you learn how to use them more effectively. You may also consider working in an entry-level role or completing an internship in such departments to learn practical skills.

Prepare your questions

The interview is also an opportunity for you to get answers to position or organisation-related questions. It is often helpful to come prepared with thoughtful questions to ask. You may bring a printed sheet or a notepad containing questions for the interviewer. This also helps convey your initiative, professionalism and strong interest in the role.