Data Engineer Interview Questions

Today, I decided to write about the data engineering interview process and some of the topics you should be familiar with. The entire process usually takes about four interviews on average.
The first interview is a 15–30-minute phone screen with a recruiter. The recruiter will go over the position you’re applying for and then ask you some questions. Often, the recruiter is trying to assess how technical you are and whether you’d be a good fit for the role. The questions depend on the position you’re applying for, but some common ones include:

• How do you ensure data quality in your ETL process?

• How do you ensure your data pipeline is scalable and reliable?

• How do you ensure data security?

• How do you optimize your SQL queries?

The recruiter might also review the skills listed on your resume to confirm your familiarity with them."

Some non-technical questions would be:

• Tell me about yourself.

• Why are you looking to leave your current job?

• What do you expect from this new job/company?

• What are your salary expectations for this position? (Try to find out the salary range for this position first and then say a range instead of a specific number)

In the next round, you’ll meet the hiring manager or the director of analytics. Often, you’ll encounter some of the same questions asked by the recruiter. The hiring manager will focus less on technical questions and more on your past projects and details from your resume. At this stage, they’re trying to get to know you and evaluate the projects you’ve worked on to determine if you’re a good fit for the role. Always have a few projects you’ve worked on ready to discuss, and provide as much detail as possible. Highlight your successful past projects, but if something was challenging, explain how you overcame the challenge.

Here are some common questions you might encounter:

• Tell me about yourself.

• What is your greatest weakness? (I’m not a fan of this question, but I’ve been asked it.)

• How would your coworkers or supervisor describe you in one word?

• I see this on your resume—tell us about it.

• Are you familiar with cloud platforms?

• How do you handle missing data?

• What are your first steps when analyzing data?

• What type of data (industry-related) have you worked with in your current or past jobs?"

The next round is the technical interview. This can vary from company to company, but it generally covers topics like SQL, Python, PySpark, and system design, or a mix of these.

The format can also differ. You might work in a live coding environment or be given a 1–2-hour take-home assignment. It often starts with broad questions, such as:

• Describe a time when you had to create an ETL pipeline. What would you improve about it today?

• What’s the difference between unstructured and structured data?

• How would you optimize SQL queries?

For Python, be sure to know Pandas, including how to filter data, use GROUP BY-like operations, and calculate metrics like maximum or average values. StrataScratch, DataLemur, and LeetCode are great resources for practice. You should also be comfortable casting date and time values or converting integers to strings. Additionally, you might face a few Python-specific questions (outside of Pandas), such as how to create a loop or define a function.

If you don’t understand a question, feel free to ask for clarification. For Python, the interviewer might allow you to look up specific methods in the Pandas documentation using Google, but always ask permission first.

For SQL, make sure you’re proficient with DISTINCT, GROUP BY, WHERE, and HAVING clauses, as well as different types of JOINs.

The final round of interviews involves meeting the business stakeholders. These questions will focus more on business-related topics and will often tie back to your projects, so be sure to provide as many details as possible. Here are some examples:

• Tell us about a time when you faced challenges in a project and how you overcame them.

• Describe a project where you made a significant impact.

• How have you added value to a business through your data engineering work?

• How would you work with multiple stakeholders who have different requests?

• How would you explain technical concepts to non-technical people?

Always display confidence and positivity during the interview. Avoid speaking negatively about yourself or your past or current employer. If they ask about a skill you don’t have, emphasize that you’re a fast learner and willing to master new tools.
Good luck!

What’s your experience with interviews? Share your thoughts in the comments!