Databricks Data Analyst Interview Questions + Guide in 2025

Databricks is a leading data and AI company that empowers organizations to unify and democratize their data, analytics, and AI through its innovative Data Intelligence Platform.

The Data Analyst role at Databricks is pivotal in harnessing the power of data to drive strategic decision-making and operational efficiencies. This position primarily involves analyzing B2B sales, marketing, or finance data and providing actionable insights through the creation of dashboards, reports, and models. As a Data Analyst, you will collaborate closely with various teams, including Strategy and Operations, to understand their analytical needs and deliver the necessary support. You will be expected to be proficient in SQL and visualization tools such as Tableau and Databricks AI/BI, as well as have a solid understanding of CRM systems like Salesforce.

Key responsibilities include managing the requirements gathering process, executing strategic analytic projects, and maintaining strong relationships with stakeholders. Your ability to work independently, coupled with a keen understanding of data flow across systems, will be essential in this role. The ideal candidate will have a passion for data visualization and user experience, as well as a collaborative spirit that thrives in a dynamic environment.

This guide aims to equip you with insights and tailored strategies to excel in your interview for the Data Analyst position at Databricks, helping you to articulate your experience and showcase your fit for the company’s innovative culture.

In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at Databricks. The interview will likely focus on your technical skills, analytical thinking, and ability to communicate insights effectively. Be prepared to demonstrate your knowledge of data analysis tools, visualization techniques, and your understanding of business operations.

Technical Skills

1. What is the purpose of the TCPDUMP command, and how would you use it in data analysis?

Understanding network data and how to capture it is crucial for a data analyst, especially in a tech-driven environment like Databricks.

How to Answer

Explain the function of TCPDUMP in capturing and analyzing network packets. Discuss scenarios where you might use it to troubleshoot data flow issues.

Example

“The TCPDUMP command is used to capture and analyze network packets. In a situation where I suspect data loss or delays in data transfer, I would use TCPDUMP to monitor the packets being sent and received, allowing me to identify any anomalies in the data flow.”

2. Can you explain the difference between structured and unstructured data?

This question assesses your understanding of data types, which is fundamental for any data analyst.

How to Answer

Define both types of data and provide examples of each. Highlight the implications of working with each type in analysis.

Example

“Structured data is organized in a predefined format, such as tables in a relational database, making it easy to analyze. Unstructured data, on the other hand, lacks a specific format, like emails or social media posts, which requires more complex processing techniques to extract insights.”

3. Describe your experience with SQL and how you have used it in your previous roles.

SQL is a critical skill for data analysts, and this question allows you to showcase your proficiency.

How to Answer

Discuss specific SQL queries you have written, the complexity of the data you worked with, and how your SQL skills contributed to your analysis.

Example

“I have extensive experience using SQL for data extraction and manipulation. For instance, I wrote complex queries to join multiple tables and aggregate sales data, which helped my team identify trends and make data-driven decisions.”

4. How do you ensure data accuracy and integrity in your analyses?

This question evaluates your attention to detail and understanding of data quality.

How to Answer

Discuss the methods you use to validate data, such as cross-referencing with other sources or implementing data cleaning processes.

Example

“To ensure data accuracy, I implement a multi-step validation process. This includes cross-referencing data with original sources, using automated scripts to identify anomalies, and conducting regular audits to maintain data integrity.”

5. What visualization tools have you used, and how do you choose the right one for a project?

This question assesses your familiarity with data visualization tools and your ability to communicate insights effectively.

How to Answer

Mention specific tools you have used, the types of visualizations you created, and how you determined which tool was best suited for the project.

Example

“I have used Tableau and Databricks for data visualization. I choose the tool based on the audience and the complexity of the data. For instance, I used Tableau for interactive dashboards that required user engagement, while I opted for Databricks for its seamless integration with our data pipeline.”

Analytical Thinking

1. Describe a challenging data analysis project you worked on. What was your approach?

This question allows you to demonstrate your problem-solving skills and analytical mindset.

How to Answer

Outline the project, the challenges faced, and the steps you took to overcome them, emphasizing your analytical process.

Example

“I worked on a project analyzing customer churn rates, which was challenging due to incomplete data. I first identified the missing data points and collaborated with the data engineering team to fill in the gaps. Then, I applied statistical methods to analyze the churn patterns, which led to actionable insights for the marketing team.”

2. How do you prioritize tasks when working on multiple projects?

This question assesses your project management skills and ability to handle competing priorities.

How to Answer

Discuss your approach to prioritization, such as using a matrix or considering deadlines and impact.

Example

“I prioritize tasks by assessing their urgency and impact on the business. I use a prioritization matrix to categorize tasks and focus on high-impact projects first, ensuring that I meet deadlines while delivering quality analyses.”

3. Can you give an example of how you turned data into actionable insights?

This question evaluates your ability to translate data findings into business strategies.

How to Answer

Provide a specific example where your analysis led to a significant business decision or improvement.

Example

“In a previous role, I analyzed sales data and identified a trend where certain products were underperforming in specific regions. I presented my findings to the sales team, which led to targeted marketing campaigns that increased sales by 20% in those areas.”

4. How do you handle feedback on your analyses?

This question assesses your openness to collaboration and improvement.

How to Answer

Discuss your approach to receiving feedback and how you incorporate it into your work.

Example

“I view feedback as an opportunity for growth. When I receive feedback, I take the time to understand the perspective of my colleagues and make necessary adjustments to my analyses. This collaborative approach often leads to more robust insights.”

5. What methods do you use to stay updated on industry trends and data analysis techniques?

This question evaluates your commitment to continuous learning and professional development.

How to Answer

Mention specific resources, such as online courses, webinars, or industry publications, that you use to stay informed.

Example

“I regularly read industry publications like Harvard Business Review and participate in webinars on data analysis techniques. Additionally, I take online courses to learn new tools and methodologies, ensuring that I stay current in this rapidly evolving field.”

Here are some tips to help you excel in your interview.

Understand the Technical Landscape

Familiarize yourself with the technologies and tools that Databricks utilizes, particularly the Data Intelligence Platform, SQL, and visualization tools like Tableau. Given the emphasis on technical skills in the role, being able to discuss your experience with these tools and how you have used them to derive insights from data will be crucial. Additionally, understanding how data flows between systems like Salesforce and Xactly will help you demonstrate your readiness to tackle the responsibilities of the role.

Prepare for Theory-Based Questions

Expect a significant focus on theoretical knowledge during the interview. Review key concepts related to data analysis, data governance, and analytics methodologies. Be prepared to answer questions that may require you to recall specific definitions or functions, such as the purpose of commands like TCPDUMP. Practicing with multiple-choice questions can also help you get comfortable with the format and time constraints you may encounter.

Showcase Your Analytical Mindset

During the interview, emphasize your analytical thinking and problem-solving skills. Be ready to discuss past projects where you successfully built dashboards or conducted analyses that provided actionable insights. Highlight your ability to translate complex data into understandable visualizations and how your work has positively impacted business decisions. This will demonstrate your alignment with Databricks' mission to simplify the data lifecycle.

Emphasize Collaboration and Stakeholder Engagement

Databricks values collaboration and relationship-building across teams. Be prepared to discuss how you have worked with various stakeholders in previous roles, particularly in gathering requirements and executing projects. Share examples of how you have navigated challenges in team dynamics or project management, showcasing your service-oriented mindset and ability to foster a collaborative environment.

Align with Company Culture

Databricks prides itself on a diverse and inclusive culture. During your interview, reflect on how your values align with this commitment. Be ready to discuss how you have contributed to a positive team environment in the past and how you plan to continue doing so at Databricks. This will not only show that you are a good fit for the company culture but also that you are invested in fostering inclusivity within your team.

Practice Clear Communication

As a Data Analyst, your ability to communicate complex data insights clearly is essential. Practice articulating your thoughts in a structured manner, ensuring that you can explain your analyses and findings in a way that is accessible to both technical and non-technical audiences. This skill will be vital in your interactions with stakeholders and in presenting your work.

By following these tips and preparing thoroughly, you will position yourself as a strong candidate for the Data Analyst role at Databricks. Good luck!

The interview process for a Data Analyst role at Databricks is structured to assess both technical skills and cultural fit within the organization. It typically consists of several key stages:

1. Initial Screening

The first step in the interview process is an initial screening, which usually takes place via a phone call with a recruiter. This conversation lasts about 30 minutes and focuses on your background, experience, and understanding of the Data Analyst role. The recruiter will also provide insights into Databricks' culture and values, ensuring that you align with the company's mission and vision.

2. Technical Assessment

Following the initial screening, candidates will undergo a technical assessment. This may be conducted through a timed online test or a video interview. The assessment is designed to evaluate your analytical skills and knowledge of data analysis concepts. Expect questions that cover theoretical aspects of data analysis, including statistical methods, data visualization techniques, and SQL queries. You may also encounter scenario-based questions that require you to demonstrate your problem-solving abilities.

3. Behavioral Interview

After successfully completing the technical assessment, candidates will participate in a behavioral interview. This round typically involves one or more interviewers from the analytics team and focuses on your past experiences, teamwork, and how you handle challenges. Be prepared to discuss specific examples of how you have collaborated with stakeholders, managed projects, and derived insights from data in previous roles.

4. Final Interview

The final interview stage may include a presentation component, where you will be asked to present a case study or a project you have worked on. This is an opportunity to showcase your analytical skills, communication abilities, and how you can translate complex data into actionable insights. Additionally, you may meet with senior leadership or cross-functional team members to discuss your fit within the broader organization.

5. Offer and Negotiation

If you successfully navigate the previous stages, you will receive an offer. This stage may involve discussions around compensation, benefits, and other employment terms. Databricks values transparency in its compensation practices, so be prepared to discuss your expectations and any questions you may have about the offer.

As you prepare for your interview, consider the types of questions that may arise during each stage of the process.

1. Develop a function str_map to determine if a one-to-one correspondence exists between characters of two strings at the same positions.

Given two strings, string1, and string2, write a function str_map to determine if there exists a one-to-one correspondence (bijection) between the characters of string1 and string2.

2. Design three classes: text_editor, moving_text_editor, and smart_text_editor with specific functionalities.

Design three classes: text_editor, moving_text_editor, and smart_text_editor. Implement methods for writing, deleting, and special operations as defined. Ensure moving_text_editor and smart_text_editor extend text_editor with additional functionalities.

3. Write a function sum_pair_indices to find indices of two integers in an array that add up to a target integer.

Given an array and a target integer, write a function sum_pair_indices that returns the indices of two integers in the array that add up to the target integer. Ensure the solution works in O(n) time.

4. Write a query to show the number of users, transactions, and total order amount per month in 2020.

Write a SQL query to show the number of users, number of transactions placed, and total order amount per month in the year 2020. Use the transactions, products, and users tables.

5. Write a SQL query to compute the cumulative sum of sales for each product, sorted by product_id and date.

Write a SQL query to compute the cumulative sum of sales for each product, sorted by product_id and date. Use the sales table to track every purchase made on the store.

6. Is this a fair coin?

You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if the coin is fair based on this outcome.

7. What is the probability that a user has exactly 0 impressions?

You have an audience of size A and a limited amount of impressions B. Each impression goes to one user at random. Calculate the probability that a user receives exactly 0 impressions.

8. How would you determine if a two-sided coin is biased?

You are given a two-sided coin that could be fair or biased. Design a test to figure out if the coin is biased and describe the outcome that would indicate bias.

9. What is the probability that a user views more than 10 ads a day?

Users view 100 posts a day on a social media website, with each post having a 10% chance of being an ad. Calculate the probability that a user views more than 10 ads a day and approximate this value using the standard normal distribution’s cdf.

10. Which Facebook Ads payment option should you choose and why?

You have two options for paying Facebook Ads for your e-commerce product growth: - Pay within 90 days with a 6% fee on the principal. - Pay within 45 days with a 3% fee on the principal. Determine which option to choose and explain your reasoning.

11. What metrics would you use to track the accuracy and validity of a spam classifier model?

You are tasked with building a spam classifier for emails and have built a V1 of the model. What metrics would you use to track the model’s accuracy and validity?

12. How would you build a model to bid on a new unseen keyword?

You are working on keyword bidding optimization with a dataset containing keywords and their bid prices. How would you build a model to bid on a new, unseen keyword?

13. How would you build a fraud detection model with a text messaging service for transaction approval?

You work at a bank that wants to detect fraud and implement a text messaging service to allow customers to approve or deny transactions flagged as fraudulent. How would you build this model?

14. Why has the number of job applicants been decreasing despite stable job postings?

You are analyzing a job board where job postings per day have remained constant, but the number of applicants has been decreasing. What could be the reasons for this trend?

15. What considerations should be made when testing hundreds of hypotheses with many t-tests?

You are conducting numerous t-tests to test various hypotheses. What factors should you consider to ensure the validity and reliability of your results?

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your Databricks data analyst interview include:

• Prepare on Multiple Domains: Databricks focuses heavily on theory questions which are more about what you know than practical application. Review concepts like ACID properties, data cleaning methods, and key SQL/Python commands.
• Know Databricks Tools: Familiarize yourself with Databricks’ platform and complimentary technologies. Knowing tools like Tableau, Databricks AI/BI, and supplemented CRM systems will give you an edge.
• Expect Rescheduling: Based on past experiences reported, the hiring process might go through sudden rescheduling. Stay flexible and hopeful because external factors like hiring freezes can influence timing.

What is the average salary for a Data Analyst at Databricks?

According to Glassdoor, Data Analysts at Databricks earn between $121K to $178K per year, with an average of $146K per year.

What skills are required for a Data Analyst at Databricks?

To excel as a Data Analyst at Databricks, you need 5+ years of experience working with B2B sales, marketing, or finance data. Proficiency in SQL, data visualization tools (e.g., Tableau, Databricks AI/BI), and an understanding of CRM systems like Salesforce are important. Experience with Databricks, CRM Analytics, and Python is an added advantage.

What kind of projects will I work on as a Data Analyst at Databricks?

At Databricks, you’ll be engaged in building analytic tools like dashboards, tables, analyses, and models. These tools will support hundreds of employees, including technical and non-technical sales teams, as well as company leaders globally. You’ll also manage strategic analytic projects and collaborate with stakeholders to provide visibility and insight into business operations.

What benefits does Databricks offer for the Data Analyst role?

Databricks offers a comprehensive benefits package including medical, dental, and vision insurance, a 401(k) plan, flexible time off, paid parental leave, family planning assistance, fitness reimbursement, annual career development fund, and mental wellness resources, among others.

Preparing for a Data Analyst position at Databricks can seem daunting, given the rigorous interview process and high expectations. However, with the right preparation and mindset, you can navigate through it successfully. To enhance your readiness, consider practicing with Interview Query, which provides in-depth guides on Databricks’ interview process. From understanding SQL and Python basics to grasping complex analytic tools and visualization techniques, these resources are invaluable.

If you want more insights about the company, check out our main Databricks Interview Guide, where we have covered numerous interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Databricks’ interview process for different positions.

Good luck with your interview!