Why this matters:
Different volumes of data require different toolsets. This question can help you evaluate the depth of a candidate’s experience and their level of familiarity with the tools your company uses every day. A great data engineer will be able to tell you which tools need to be applied and when.
What to listen for:
- Experience working on projects similar in scope and scale to the demands of the job
- Examples of specific tools used in previous roles and why the candidate chose them
- Interest in learning new tools and expanding capabilities to handle larger volumes of data
Why this matters:
Even if their previous company was very different from your own, you want to know your new hire can apply transferable skills and experiences to the position. Whether your candidate brings a coding background, strong proficiency in SQL database manipulation, or just a general knack for aligning datasets with company goals, these technical abilities can facilitate easy onboarding and help your company grow stronger.
What to listen for:
- Technical proficiencies relevant to the role or that fill current gaps
- Examples of how their unique experience, skills, or viewpoint can benefit your company
- Aptitude for learning new skill sets and commitment to professional development
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 goes above and beyond the specific tasks they’re assigned to proactively seek out answers to big picture questions.
What to listen for:
- Experience in a leadership role or working as part of a team
- Communication and interpersonal skills, along with a professional manner of speaking
- Conveyance of enthusiasm, passion, initiative, or thirst for knowledge
Why this matters:
ETL stands for extract, transform, and load — the three key steps for designing and structuring most data pipelines. You want a new hire who is familiar with the operational aspects of data engineering, such as code reliability. 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:
- Experience putting critical-thinking skills to work to identify and solve a challenge
- Solutions comparable with the best practices your top data engineers follow
- Description of specific tools used to fix the ETL issue and why they were selected
Why this matters:
Good code is reusable. All data engineers know that, but not all of them stop and consider whether 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:
- A clear understanding of the value of using existing code
- Experiences that reflect a desire to save the company time and money
- Resourcefulness and creative out-of-the-box thinking
Why this matters:
This answer will help you gauge the candidate’s leadership potential and current level of experience handling complex tasks. Data engineers must be resilient, often thinking on their feet and adapting to sudden deviations from the original path. From deadline pressure and technical inefficiencies to communication gaps and tedium, there’s no shortage of challenges to choose from, but a strong candidate stays positive.
What to listen for:
- Demonstrated ability to take charge and rally everyone around common goals
- Examples of common challenges encountered and how the candidate solved them
- Positive description of lessons learned, skills acquired, or takeaways
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:
- Genuine enthusiasm for the field of data engineering
- Assignments that align with the candidate’s professional aspirations
- Curiosity, willingness to learn, and a goal-oriented mindset
Why this matters:
Asking this question explores what a candidate finds challenging and reveals potential areas where more training is required. This question also screens for humility, self-reflection, and problem-solving skills. A great data engineer will view obstacles as an opportunity to learn and grow more confident.
What to listen for:
- Description of minor setbacks that are unlikely to affect the candidate’s performance
- Transparency and indication that the candidate is not easily defeated by challenges
- Steps taken to mitigate issues and improve in areas of perceived weakness
Why this matters:
This question reveals the candidate’s communication skills and 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 confidently, you know that this candidate will be able to liaise with less technically minded leaders and coworkers.
What to listen for:
- Ability to translate complex concepts into everyday language
- Demonstrated public speaking and presentation skills
- Experience or interest in collaborating across various departments
Contact a sales specialist.