Data Analyst Interview Questions

Once you have secured an interview for a Data Analyst position, there are few things you can do to prepare. You will want to:

• Research the company
• Review your data knowledge, skills, and projects
• Practice some common Data Analyst interview questions

Interview questions for Data Analyst positions will focus on both your technical skills and soft skills. The questions may range from testing your knowledge to learning about your past work and assessing how you would fit in with the company.

This will help you focus your interview preparation. For instance, if the role involves data cleaning, think about specific examples of how you have cleaned data in the past, and practice explaining your process.

To help you prepare for your interview, we have put together a list of commonly asked Data Analyst interview questions.

To see whether you have the necessary knowledge to excel at a Data Analyst job, employers may ask questions that test your understanding of processes and tools like SQL, Excel, statistical programming, and data visualization.

Hiring managers use these data analysis interview questions to mainly gauge your knowledge level, while also getting a better sense of your data analysis process and overall perspective on your job responsibilities.

Here are some examples of common skills-based Data Analyst interview questions and how you can answer them:

Question: What do Data Analysts do?

Answer: This question is specifically geared toward getting a better sense of your own opinion on the expectations of the role, so your answer should not only be derived from your own job experience in your Data Analyst career, but also on the specific expectations that were listed in the job description.

Although the specifics of your answer will obviously differ, Data Analysts mainly:

• Analyze and interpret data
• Use those insights to make actionable recommendations and reports to build revenue and improve processes

Question: What are the important steps in the data validation process?

Answer: The first section of Data Analyst interviews might feel a bit like a pop quiz, but even if you’re a relatively experienced Data Analyst, it’s important to be able to answer knowledge questions like this one in a clear and easy-to-understand way. So you could first explain that to validate data – or, in other words, to review the quality of source data – you first perform data screening by using different algorithms to scan a data set for issues. Then, you evaluate any data values you suspect might be inaccurate before deciding whether or not to use them.

What is the data analysis process?

What is your approach to cleaning data?

Define the difference between data profiling and data mining?

If a Data Analyst has missing or suspected data, what should they do?

Please outline the different data validation methods used by Data Analysts.

What are the properties of clustering algorithms?

Define a hash table collision. How can it be prevented?

What’s your approach to multi-source problems?

What problems could a Data Analyst face while performing data analysis?

What are the characteristics of a good data model?

Explain the difference between variance and covariance.

Explain univariate, bivariate, and multivariate analysis.

What are the advantages of version control?

You should also be able to define and explain a number of terms, including:

Employers will likely ask questions that put your technical Data Analyst skills to the test.

They may want to know about your past experience with certain programs or tools, or they may ask you to solve a problem on the spot.

For this type of Data Analyst interview question, it also doesn’t hurt to talk a bit about how you acquired these technical skills.

This provides another opportunity to talk about past work experience or your educational background, while also pointing out some examples of you applying these skills to real-world projects.

Here are some examples of common technical Data Analyst skills questions that an interviewer may ask and how you can answer them:

Question: What data analytics tools do you use?

Answer: This is another interview question where it will work in your favor to review the job description and look at the specific technical competencies that are demanded. But most Data Analysts use various tools and software programs to accomplish their day-to-day job responsibilities.

To create eye-catching visualizations, most Data Analysts are experienced with:

Most Data Analysts are also familiar with programming languages and frameworks including:

They also know their way around data analysis platforms including Google Analytics and Adobe Analytics. It will likely also be worth mentioning spreadsheets and querying languages commonly used by Data Analysts, such as XML and SQL.

What’s your approach to dealing with messy data?

What’s your favorite data analysis software to use?

How do you evaluate if a developed data model is good or not?

Tell me about your most recent data analysis project. Did it challenge you in a different way than other data analysis work you’ve done in the past?

What are some of your data analysis best practices?

Can you think of a time you used quantitative and qualitative data within the same project?

What’s the largest data set you’ve worked with? How many entries and * variables did the data set comprise? What kind of data was included?

Tell us about your educational experience with statistics. Have you used it in your work as a Data Analyst?

In your projects as a Data Analyst, what scripting languages have you used?

You’ve received a data set with suspicious or missing data. What do you do next?

Tell us about your SQL programming experience. How many analytical projects have you completed using SQL?

Have you ever created or worked with statistical models? How have the models helped you solve a business problem?

What data analytics tools have you used for creating dashboards?

How do you use Excel as an analytical tool in your projects? Which Excel functions do you use most often in projects?

Explain how you would estimate how many jackets could potentially be sold in New York City every September.

How would you approach measuring the business performance of our company? What metrics would you use and what information would be the most important to consider?

Personal questions are a way for employers to get to know your personality, work habits, and goals. Personal interview questions can help the interviewer assess how you may fit into their company’s work culture.

Here is an example of a personal interview question a Data Analyst might be asked (and how you can answer it):

Question: Why did you decide to become a Data Analyst?

Answer: Put your storytelling hat on and take the interviewer through your career and how you wound up working in data analytics. It’s a personal question so you will also have a personal answer, but as you discuss your journey, try to weave in specific projects you worked on that confirmed your interest in data analytics (along with the outcomes of those projects).

Other reasons you might be interested in data analytics could include your love of:

• Crunching numbers
• Problem-solving
• Creating compelling and stimulating visualizations to communicate complex ideas

Tell me about yourself.

If you had to specialize, which area of data analytics would you prefer to work in? Why?

Which data analytics project are you most proud of?

How do you handle pressure and stress?

What are your long-term data analysis goals?

What would you bring to our company? Why would it be a good decision to hire you?

Why does our company interest you?

Please tell me about your passions.

Do you have any professional credentials or data analytics certifications to validate your skills or boost your career opportunities as a Data Analyst?

What is your greatest strength as a data professional?

What is your greatest weakness?

What kind of work environment do you feel most comfortable in?

What part of a data analysis project do you enjoy the most?

How do you measure success?

Successful Data Analysts have the necessary leadership and communication skills to make decisions, solve problems, and share insights and findings.

Here is an example of a situational Data Analyst interview question and how you can answer it:

Question: As a Data Analyst, have you ever recommended a change to different tools or techniques? What was the outcome?

Answer: If it’s the job of a Data Analyst to unearth hidden trends and insights, then make smart recommendations based on those insights, then it’s also important for a Data Analyst to be able to speak up and initiate change in an organization.

With this question, a hiring manager will be looking to see whether you’re the type of difference-maker who can innovate a company’s processes without worrying too much about rocking the boat.

Try to provide a specific example of when you identified an opportunity to improve the way an organization was operating, along with the outcome.

What are your top communication skills?

Please provide an example of a situation in which you demonstrated leadership capabilities on the job?

Describe a time when you had to persuade others. How did you get buy-in?

Please provide a self-assessment of your writing skills? As a Data Analyst, why is written communication important?

Have you ever had to present to an audience of stakeholders who didn’t understand data analysis or what a Data Analyst does? How did you explain your insights and processes?

A candidate’s past job experiences can reveal a lot about their skills, knowledge, and abilities. For behavioral interview questions, you will want to provide specific examples of situations, as well as lessons you learned or skills you gained.

Here is an example of a behavioral interview question for a Data Analyst and how you can answer it:

Question: Describe your experience sharing your insights in presentations?

Answer: It’s not just enough for a Data Analyst to be adept at creating brilliant visualizations – they also must have the communication skills and confidence to present that information in front of diverse, sometimes intimidating audiences.

Increasingly, employers will also want to know that you’re comfortable presenting both in-person and virtually. Though it’s hard to quantify success or outcomes in your presentations, you could talk about how much you enjoy getting the chance to go into detail on your work.

Another way to score points with interviewers: mention how you pride yourself on creating presentations that can be understood and appreciated by all audiences, regardless of their technical background. After all, it’s generally much more likely that you will be presenting to audiences of laypeople than other data science or data analytics professionals.

Please provide a specific example of a time you failed to meet a deadline. What happened, and what would you do differently next time?

Do you have good data sense? Why or why not?

Have you ever had to work with stakeholders who had a limited technical background and understanding of data and databases? How did you handle this challenge?

Why is creative thinking an important quality for Data Analysts?

Have you ever run an analysis on the wrong set of data? How did you figure out your error?

Think back to the most complex data analysis project you have completed. What were the most difficult challenges you faced, and how did you overcome them?

When you design an experiment, how do you measure success?

Data analysis is a rapidly growing field, and companies are increasingly looking to hire the best talent to handle big data. Here are a few examples of interview questions for Data Analysts from some of the top tech companies (including Amazon, Google, Facebook, Microsoft, and more):

Here are some common tech interview questions for Data Analysts:

Please explain the difference between clustered and non-clustered indexes in SQL?

What data cleansing techniques do you use?

How do you define data normalization and non-normalization?

Please explain what cascading referential integrity means.

What’s your time management approach for solo projects?

Are there specific functions in SQL that you use the most?

Please provide an example of a situation in which you automated an otherwise manual process.

Do you recall a time when you expected one thing when you began an analysis, but then got results you didn’t anticipate?