Why this matters

This question can help you evaluate a candidate’s experience and their level of understanding and familiarity with the tools your company uses every day. Different volumes of data require different toolsets. A great data engineer will be able to tell you which tools need to be applied and when.

What to listen for

  • Probe for examples of specific tools used in previous roles and why the candidate chose them.
  • Candidates should show interest in learning new tools and utilizing ones they may not be as passionate about.

Why this matters

Even if their previous company was very different to your own, you want to know your new hire can pull from their own experience, analyze the information, and put it into a new paradigm. This will not only smooth the onboarding process, but will help your company grow stronger by gaining a new perspective.

What to listen for

  • Great candidates will provide examples of how their unique experience, skills, or viewpoint will benefit your company.
  • Look for signs that their work style blends well with your corporate culture.

Why this matters

Data engineers have to work well with people throughout the organization to understand the business questions they’re trying to solve. You want to hire someone who seeks out those answers proactively and cares about the big picture, rather than focusing solely on the specific tasks they’re assigned.

What to listen for

  • Listen for evidence of passion, initiative, and a thirst for knowledge.
  • Answers like “I just create the data and leave it to the data scientist to analyze,” could indicate a lack of initiative or interest.

Why this matters

ETL stands for Extract, Transform and Load—the three key steps for designing and structuring most data pipelines. You want to feel confident that your new hire is familiar with the operational aspects of data engineering, such as the reliability of your code. Asking this question will also help you get a sense of what performance means to candidates and how they're measuring it.

What to listen for

  • Answers should cover the specific tools they used and why.
  • Listen for solutions that are comparable with the best practices your top data engineers follow.

Why this matters

Good code is reusable. All data engineers know that, but not all of them have the professional maturity to stop and consider if there are assets in the company code vault that can be re-used for a different purpose. If you find you’re talking to a data engineer whose first order of business is to peruse through your existing database before jumping into writing code on a new project, you may have a winner.

What to listen for

  • Candidates should demonstrate a clear understanding of the value of using existing code.
  • Top answers will reveal a desire to find ways to save time and money for the organization.

Why this matters

This answer will help you gauge the candidate’s level of experience with difficult tasks and their approach to dealing with problems. It can also reveal leadership potential. When times get tough, is the candidate a leader or a follower? Are they content just doing their part to see a project to completion, or do they actively drive the success of the entire team?

What to listen for

  • Look for candidate’s with a demonstrated ability to take charge and rally everyone around them.
  • Answers should include examples of common problems encountered and how they dealt with them.

Why this matters

Studies show that people who are passionate about what they do and take pride in their successes often make the best employees, regardless of the situation, project, or role. Whether it’s a worthy data project or an employee they helped mentor, a candidate’s answer will help you understand what motivates and excites them.

What to listen for

  • Candidates should show genuine enthusiasm for the field of data engineering.
  • An ideal answer will align closely with the type of work your new hire will do on a regular basis.

Why this matters

This question screens for humility, self-reflection, and problem-solving skills. Everyone makes mistakes sometimes, but it’s how a candidate responds to them that matters. A great data engineer will view their missteps as an opportunity to learn and their work will become stronger for it.

What to listen for

  • Look for transparency and an indication that the candidate is not embarrassed by failure, but sees it as a necessary part of growth.
  • Great answers will outline steps they’ve taken to avoid making the same mistake again or improve their work now that they know better.

Why this matters

This will tell you all you need to know about a candidate’s ability to talk to colleagues who don’t live and breathe data. Can they convey technical or complex concepts clearly and concisely? If they answer well, you know that this candidate will be able to liaise with less technically minded leaders and coworkers, like those working in the finance department or HR.

What to listen for

  • Candidate’s should have a clear ability to translate complex concepts into everyday language.
  • Ideal answers will demonstrate experience collaborating across various departments.