On average, there are up to 100,000 job openings for data analysts worldwide, with demand from top industries, including Finance, Healthcare, and Entertainment. If you’re looking to move into this sought-after career or move up the professional ladder, you’ll need to prepare for the process, including how to answer your data analyst interview questions. This article has everything you need to succeed.
For those looking for information about starting your career, you can learn how to become a data analyst in a separate article.
Typical Data Analyst Interview Process
The data analyst interview process typically involves the following steps:
- HR Interview: Your first step will often involve a screening call with a recruiter to get a sense of your experience, interest, and salary expectations, as well as provide you with details about the position.
- Hiring Manager Interview: The next call is normally with the hiring manager. They might ask more about your direct experience, as well as why you are interested in the position.
- Technical Screen: This part is specific to data analyst roles. The technical interview can involve SQL and Python questions or a take-home test.
- On-site interview: The final step tends to focus on your business acumen.
Once you have passed through these core parts of the interview process, you may have to wait for an offer. Regardless of whether you get the job or not, you may get a chance for feedback, which can be helpful for your career.
Data Analyst Interview Questions and Answers
Let’s take a look at some of the questions the interviewer may ask you during the data analyst interview process. Preparing your answers ahead of time can help you feel more comfortable going into the interview and also means you can adjust your answers with relative ease, depending on the questions you’re asked.
General data analyst interview questions
These are some of the questions you might encounter early on during the interview process, usually in the HR interview. They are often the data analyst behavioral interview questions used to determine what kind of professional you are and how much you understand about the role and the company:
1. Tell me about yourself
Despite being a relatively simple question, this one can be hard for many people to answer. Essentially, the interviewer is looking for a relatively concise and focused answer about what’s brought you to the field of data analytics and what interests you about this role.
You should focus on why data analytics is meaningful to you, what excites you about this specific role, and what you’re hoping to gain from it.
2. What makes you the best candidate for the job?
Although this can be a broad question, remember the interviewer wants to hear about you as a data analyst. So consider your journey with data analysis, what got you interested in the first place, your previous experience, and why you are applying for this role in particular.
3. Tell me how you coped with a challenging data analysis project
Here, the interviewer is essentially asking how you overcome challenges, giving you a chance to highlight your strengths in action. Make sure to talk about some of your strengths and weaknesses that you're working to improve.
Be honest about what went wrong or what you found difficult, and try to highlight any skills listed in the job requirements of this role. Again, make sure you give an answer with a positive outcome, showing the lessons/skills you learned to cope with similar challenges in the future.
The interviewer may instead ask you to talk about a successful project, but your approach should be the same either way. Give a specific example, highlight what went well and what was challenging, and mention the lessons you learned.
4. What type of data have you worked with?
This question asks you to be as specific as possible. Focus on the size and type of data you have worked with, whether from previous work experience or your own projects and programs. Many hiring managers will be looking to see if you can handle large, complex data.
You can draw on all kinds of examples here, whether it’s career-related or something that’s part of a personal project or online course.
Data analyst process interview questions
In your day-to-day work as a data analyst, you’ll spend a lot of time working on various tasks and processes. During the hiring manager interview, you’ll likely encounter questions about processing, including:
5. What is data cleaning, and how do you do it?
Data cleaning (also known as data preparation or data cleansing) takes up a large part of your work hours as a data analyst. When you answer this question, you can show the interviewer how you handle the process. You’ll want to explain how you handle missing data, duplicates, outliers, and more. Be sure to explain why it is important and how you have dealt with it in past projects.
6. How do you communicate technical concepts to a non-technical audience?
Much of data analysis involves ordering your findings into a narrative and clearly explaining it to both technical and non-technical audiences. This is where your soft skills come in: communication and storytelling. Give examples of how you’ve drawn insights from data and communicated those to audiences. These might include presentations to shareholders or written communication within your portfolio.
7. How would you go about measuring the performance of our company?
When an interviewer offers up a question about the company, this is an opportunity to show your research into their work and how you align with them. Consider how your analysis skills can bring insights specific to this company in particular, with their problems and goals in mind.
8. How would you estimate…?
They may give you a situational question here, asking how you’d approach a task from start to finish. This question will test your analytical skills, as well as your ability to think on your feet. You should talk the interviewer through your approach and rely on your knowledge and skills to guide you.
Data analyst technical interview questions
9. What data analytics software are you familiar with?
This is a good opportunity to show the data analyst tools you’ve used before and any data certifications you have (such as our esteemed Data Analyst Certification). You can talk about how long you have been working with these kinds of tools and software.
This question helps the interviewer assess what level of experience you have and how much training you might need for the role in question.
You can prepare by including any software listed in the job description that you have worked with, mentioning software solutions and how you have used them for different stages across the data analysis process. Be sure to include relevant terminology to keep on track.
Software to mention for data analyst roles includes R, Python, Tableau, and Microsoft Excel. Be sure to try some extra data analyst training if you’re uncertain of these.
10. What is your statistical knowledge for data analysis?
This question is usually asking if you have a basic understanding of statistics and how you have used them in your previous data analysis work.
If you are entry-level and not familiar with statistical methods, make sure to research the following concepts:
- Standard deviation
- Sample size
- Descriptive and inferential statistics
If you do have some knowledge, be specific about how statistical analysis ties into business goals. List the types of statistical calculations you’ve used in the past and what business insights those calculations yielded.
11. Can you define these terms?
With this question, the interviewer is trying to probe your depth of knowledge. They may ask about some of the following terms and how they’re relevant to data analysis:
- Normal distribution
- Data wrangling
- KNN imputation method
- Statistical model
12. Can you explain the difference between these terms?
As with the last question, this one is designed to test how deep your knowledge goes. The interviewer may give you a few different terms to identify the differences and when to use each one. Some concepts to prepare include:
- Quantitative vs qualitative data
- Data profiling vs data mining
- Joining vs blending in Tableau
- Variance vs covariance
SQL interview questions for data analysts
SQL is one of the most sought-after skills for data analysts, so your technical interview may test your knowledge of SQL and databases. It’s worth preparing some of the essentials of SQL for data analyst roles.
13. Define a SQL term
Again, your interviewer might seek to test your understanding of SQL principles by asking about specific SQL queries and terms and what they do. It’s worth preparing your knowledge of terms such as:
- Clustered vs non clustered index
- DBMS vs RDMBS
There are plenty of other terms to cover, and you can check out our Exploratory Data Analysis in SQL course for a refresher on anything you’re lacking.
14. Write a query
As this is the technical part of the data analyst interview questions, you’ll likely need to demonstrate your skills to some degree. The interviewer may give you either a problem or a selection of data, and you’ll need to write queries to store, edit, retrieve or remove data accordingly. The difficulty of this task usually depends on the role you’re applying for and its seniority.
Questions to Ask in a Data Analyst Interview
Once you’ve successfully navigated through all of the questions the interviewer has, they’ll likely ask if you have any questions for them. You should absolutely have some prepared. Asking thoughtful and insightful questions shows that you’re interested in the role and the company, that you can think on your feet, and that you’ve prepared ahead of time.
It’s a good idea to prepare some questions in advance. However, the interviewer may cover these off during the process, so make sure you’re paying attention and mentally note down anything that crops up in the interview.
Below, we’ve outlined some questions you could ask the interviewer:
- What is the company’s culture like?
- Which data analysis tools do the team currently use?
- What types of projects will I get to work on?
- Is there any scope for mentorship or personal development?
- What are the expectations for my first week/month/quarter in the role?
- What goals or metrics will I be evaluated against?
- What’s your favorite thing about working for the company?
Tips to prepare for your Data Analyst interview
Here are DataCamp’s top tips to help you prepare for these questions and your data analyst interviews:
Research the business
Find out what the company’s problems or potential problems are. For example, what might be their current data problems? Who are their target audiences? With this research, plan how you might solve these problems using your experience.
Research the interview format
At the beginning of the process, take the opportunity to ask the recruiter for direction. Seek out interview experiences and guides using sources like Blinds or discussion posts.
Identify your top skills
Through the interview process, some meetings will be focused on certain attributes more than others. For instance, in a technical interview, you need to exhibit your experience with database languages such as SQL. Think of your skills as combined and separate. Be prepared to discuss technical skills, analytics, and visualization, as well as business acumen and soft skills.
You can read more about data analyst skills for career success in a separate article.
Study and practice interview questions
Make use of this article and the DataCamp platform to practice your technical skills, build up your project experience, and expand your portfolio. You can also work on a variety of business and analytics case studies.
A few key things to remember before, during, and after the interview
- Before: Research and practice as much as you can to align yourself, your skills, and your experience with the business and role they are offering. Consider whether the interview will be in person, ensuring you make technical checks with your video and sound if the meeting is taking place online.
- During: Stay alert to the questions being asked of you. Interviewers may ask general questions such as “tell me about yourself,” but remember all questions lead back to data analysis. You should also ask some of your own questions about the role, the business, and your goals.
- After: Follow up your interviews with thank you emails to recruiters and hiring managers. Use the opportunity to connect with them post-interview to ask for feedback or any questions you didn’t get a chance to ask during the meeting.
What are some common data analyst interview questions?
Common data analyst interview questions include asking about your experience with data analysis software, your statistical knowledge, how you communicate technical concepts to non-technical audiences, and how you would measure the performance of a company.
How can I prepare for a data analyst interview?
To prepare for a data analyst interview, research the business, study and practice interview questions, identify your top skills, and familiarize yourself with the interview format. You should also make sure to ask thoughtful questions during the interview and follow up with a thank you email afterwards.
What technical skills should I focus on for a data analyst interview?
Technical skills that are important for a data analyst interview include knowledge of data analytics software such as R, Python, Tableau, and Microsoft Excel, as well as proficiency in SQL and databases. You should also have a basic understanding of statistics and be familiar with common data analysis terms and concepts.
How can I communicate technical concepts to a non-technical audience during a data analyst interview?
To communicate technical concepts to a non-technical audience during a data analyst interview, you should focus on your communication and storytelling skills. Be prepared to give examples of how you've drawn insights from data and communicated those to different audiences, such as shareholders or colleagues.
What questions should I ask during a data analyst interview?
Some good questions to ask during a data analyst interview include asking about the company's culture, which data analysis tools the team currently uses, what types of projects you will get to work on, and whether there is any scope for mentorship or personal development. You should also ask about the expectations for your first week/month/quarter in the role and what goals or metrics you will be evaluated against.
A writer and content editor in the edtech space. Committed to exploring data trends and enthusiastic about learning data science.
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