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This post is contributed by Caroline Evans, Burtch Works’ data engineering recruiting specialist.


Data Engineering is a very technically intensive field that generally requires advanced programming skills and a vast toolkit. With that in mind, I thought I would address some of the soft skills that are critical to landing the perfect job and performing well in almost any data engineering role.

 

1. Verbal and Written Communication Skills

Increasingly, data engineering jobs require well-developed communication skills, which can sometimes be overlooked in such a technical field. A candidate can be a master programmer, but if they have trouble explaining their experience or work process, this may hold them back in their job search.

Written communication is crucial in the first few steps of the hiring process, as your resume is often the very first thing a hiring professional will see from you. Clean up your resume before you submit it to any job, and make sure to fix any grammatical, punctuation or spelling mistakes before sending it to an employer. For best practices specifically on data engineer resumes, check out this post.

Verbal communication is an especially important soft skill because it becomes apparent the moment you talk to a recruiter or hiring professional. First impressions matter, and an interviewer will notice almost immediately if a candidate has difficulty presenting their skills and experience in a concise and understandable way.

A hiring professional will be looking for a couple of specific skills during an interview, including how well a candidate can describe a project they’ve worked on. It’s generally better to start with a high-level description instead of getting bogged down in the technical details until you’re asked to expand on your experience, unless it’s a technical interview. We’re also looking to see how well a candidate can organize their thoughts and speak clearly, since this can be an essential skill when working with others on the data engineering team as well as other business units.

Here are some tips that I’ve come up with that can help data engineers improve their communication:

  • It can be helpful to write out short descriptions of your previous projects beforehand so you can prepare and become comfortable explaining your experience. It’s important to keep any descriptions concise and while you don’t necessarily need to memorize a script, practicing them can be very helpful!
  • You can also try to explain your projects or work responsibilities to someone with no technical background such as a friend or a roommate.
  • It’s also important to optimize your environment for an interview. For example, if you are conducting a phone interview, make sure you’re in a quiet place so that your interviewer can hear you clearly.

 

2. Collaboration with Other Business Units

Often, data engineers will interact with other business-oriented teams in gathering requirements and laying out the scope of a project. Because of this, it’s important for data engineers to be able to show that they understand the underlying business problem that they are working to address.

To put it simply, a data engineer needs to know and be able to articulate why they are doing what they are doing for the company at large, how their work will help the company’s bottom line, and to understand how their work is impacting the business.

3. Presentation Skills

As we’ve written about in the past, it’s becoming increasingly common for companies to include a presentation in their interview process in the data science and analytics fields. This is another way that they try to gauge a candidate’s communication skills and ability to work with business-oriented teams.

These presentations can sometimes be sharing your findings from a case study or a project you’ve done. Once complete, a candidate will typically have to explain their work to a member of the hiring team. This is another opportunity for a candidate to showcase their ability to communicate and summarize their work from a higher level. This post has several tips for professionals to keep in mind when planning presentations of technical material.

 

Strong Soft Skills are Essential for Data Engineering Leadership Roles

Generally, senior-level data engineering leadership roles will require strong communication, collaboration, and presentation skills. In order to effectively establish a data strategy or roadmap, it is often a requirement for data engineer leaders to present their plans and ideas to various business units and executive leaders. In addition, strong communication and collaboration skills are invaluable when building and mentoring a strong group of junior data engineers and will contribute to the overall team’s success.

 

We hope you found this information interesting, and if you’re looking for opportunities or to hire professionals in data engineering, be sure to connect with me on LinkedIn!

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