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data engineer interview questions - engineering interview questions

How To Prepare for Data Engineer Interview Questions

Boasting an impressive 50% year-over-year growth rate, data engineering was named the fastest-growing job in tech for 2020. 

A data engineer is basically a combination of a software developer, DevOps engineer and data scientist all rolled into one. They’re responsible for building the infrastructure that keeps a company’s most valuable resource — data — organized and for unlocking the value of that data.

Learn how to land a data engineering role by being prepared for data engineering interview questions.

Preparing for Your Data Engineering Interview

When trying to land a data engineering job, you can expect the interview process to be broken into several parts:

  • Pre-screening interview to determine potential fit. 
  • Technical pre-screen test to assess your skills. 
  • Take home tests or a test project.
  • In-person (or virtual) interview(s). 

You can expect data engineer interview questions to focus on a few key areas, so to prepare, start by thinking of examples you can share related to:

  • Coding (typically Python) including data structures, algorithms and problem solving.
  • Database design such as data modeling and data warehouses.
  • Data architecture and big data technologies with programs like Hadoop, Spark, and event processing technologies like Kafka.
  • SQL projects and examples. 

Next, you’ll want to think about your transferable skills. These are skills not specific to the role of a data engineer, but critical skills such as communication, leadership, organization and time management. 

Some of the most common data engineer interview questions you can expect are ones where you are asked to share specific scenarios that demonstrate your skills in action. These questions often start with “tell me about a time when…”.

If you have any use cases you can reference, brushing up on these while you’re prepping is a great idea. In terms of how to best answer these questions, the STAR method is designed to help you with great storytelling — focusing on the situation, task, action and result. 

Sample Data Engineer Interview Questions

Questions will likely vary depending on the specific role — questions for a senior position will be more advanced than for an entry-level data engineer position. 

Here’s our list of some data engineer interview questions you can use to help get ready for your interview. 


  • Which data engineering platforms and software are you most familiar with?
  • Which computer languages are you fluent with?
  • Do you tend to focus on pipelines, databases or both?
  • How do you create reliable data pipelines?
  • What experience do you have with data modeling?

Philosophy and Approach

  • Do you have a data engineering philosophy?
  • What common data engineering philosophy do you disagree with?
  • How would you describe having a data-first mindset? 
  • What skills do you think are most critical for data engineers? 

Use Cases and Examples

  • Tell us about a time your work made a positive impact on the company you worked for.
  • Share an example of where things went wrong during a project. How did you handle it? How did you get things back on track? 
  • Can you recall a time when you disagreed with your supervisor or coworkers on how to approach a project? How did you handle it?
  • What’s the most significant challenge you have overcome as a data engineer? 

Land Your Dream Data Engineer Role 

By having some idea of the data engineer interview questions you may be asked in your interview, you can think ahead about your answers and examples. You already have the right skills, so with a little preparation, you’ll be best positioned to wow potential employers and land your dream role in data engineering. 

Are you looking to break into the field of data engineering? Or are you an existing data engineer looking to improve your skill set so you can land your dream job? 

The Udacity Data Engineer Nanodegree Program allows students to learn to design data models, build data warehouses and data lakes, automate data pipelines and work with massive datasets. 

Jennifer Shalamanov
Jennifer Shalamanov
Jennifer is a content writer at Udacity with over 10 years of content creation and marketing communications experience in the tech, e-commerce and online learning spaces. When she’s not working to inform, engage and inspire readers, she’s probably drinking too many lattes and scouring fashion blogs.