Soft skills are highly underestimated in the tech industry. Soft skills can make the difference between stress and efficiency or being unsatisfied in your position and a raise. When data engineers earn degrees, they usually take classes in topics like data warehousing, programming, machine learning, and similar subjects. Unfortunately, most colleges and universities don’t require courses that teach the “soft skills” that can help engineers succeed.

When data professionals want to move their careers forward, they often need to learn the following six skills:

  1. Public Speaking
  2. Expository Writing
  3. Interpersonal Communication 
  4. Adaptability 
  5. Stress Management 
  6. Time Management

1. Public Speaking

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Experts believe that up to 75% of people may feel frightened of public speaking. For some, public speaking causes mild nervousness. Others feel intense fear that can prevent them from walking in front of an audience.

Without strong public speaking skills, data engineers cannot communicate their findings to managers and colleagues.

Some ways to improve public speaking skills include:

  • Spending time writing and practicing presentations.
  • Dressing professionally to feel more confident.
  • Smiling before and during the presentation.
  • Practicing in front of a mirror to gain experience.
  • Including graphics in the presentation to shift the focus from the speaker to the message.

You can also enroll in a public speaking course at a nearby college or university. Most Communications Departments will let professionals take a few classes to improve their skills.

If you feel so much anxiety that you cannot tolerate even thinking about speaking to a group, then you may want to talk to your doctor about finding a medication or counselor. Cognitive behavior therapy (CBT) works well for most people who experience anxiety in specific situations.

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2. Expository Writing 

Expository writing aims to explain or "expose" information. Data engineers need to be able to expose the important data and results to upper management. Data engineers live in a world of numbers and analytics. Managers and other business leaders don’t always have the experience needed to understand what research means. They may understand the importance of using data analytics in business intelligence, but that doesn’t mean they know how to read raw reports.

Strong writing skills require several sub-skills like:

  • Structuring sentences for clarity.
  • Organizing paragraphs so they follow a coherent thought process.
  • Summarizing complicated findings into a concise brief that readers can scan quickly.
  • Knowing when to include graphics to make results clearer.
  • Avoiding engineering jargon and excess material that waters down your main points.

The mechanics of good writing also matters. Reports with poor subject-verb agreement and other basic inaccuracies can make useful reports look unprofessional and irrelevant. Consider using an app like Grammarly, Hemingway Editor, and Readability Score to avoid common mistakes.

3. Interpersonal Communication 

Data engineers often work with machine learning engineers, data analysts, CTOs, developers, and other experts. Therefore, interpersonal communication, is an essential soft skill that can help engineers lead teams and execute projects.

Some people struggle with interpersonal communication because they consider themselves introverts. Regardless of your personality type, strong communication skills are essential.

Build your interpersonal communication skills by:

  • Using active listening to understand other perspectives.
  • Paying attention to your body language to make sure you are receptive to other people.
  • Focusing on how you present yourself to others.
  • Asking managers for constructive feedback.

Individuals accomplish more when they work with their colleagues. Remember that your job contributes to a larger goal. As your communication skills improve, you assume more leadership qualities that makes you stand out to your upper management.

4. Adaptability 

With every project there's a high chance that something will go wrong or change suddenly. Adaptability is absolutely necessary for data engineers. Learning to adapt will help you change strategies mid-project without getting too frustrated. If you don’t respond well to change, then you better learn how to.

Many professionals find that they can become more adaptable by:

  • Remembering that change isn’t personal and is inevitable.
  • Stepping back to consider why a manager may have altered the project.
  • Breaking projects into multiple stages instead of thinking of them as a single job.

Now, there are times where you shouldn't adapt. If you see a legitimate problem or negative outcome with changing strategies, then be sure to voice your concerns. 

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5. Stress Management

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According to a 2018 Gallup poll, 23% of employees say that they feel “burned out” always or very often. Nearly 45% say that they feel burned out sometimes.

People are more likely to feel burnout when they have too much work to finish, don’t understand their roles, or don’t feel supported by their managers. However, there are ways to prevent burnout like stress management. The American Psychological Association recommends managing stress by:

  • Learning healthy ways to relax, such as taking a walk, taking deep breaths, or practicing mindfulness.
  • Tracking stressors by recording thoughts and feelings in a journal.
  • Establishing borders that help maintain a work-life balance.
  • Taking time out to recharge before stress becomes a serious problem.
  • Talking to supervisors about setting expectations and defining a position’s role.
  • Planning your work ahead of time and keeping to your schedule. 

Managing stress and tracking your stressors takes practice. Commit to making changes at work and in your life so you can prevent burnout.

6. Time Management 

Time management skills can improve every aspect of your work- increasing productivity, decreasing stress, and giving you more opportunities to explore your interests.

Luckily, time management is one of the easiest skills for most data engineers to learn. It’s all a matter of practice. Some time management options that many people find useful include:

  • Prioritizing essential tasks so you don’t feel rushed at the end of the day.
  • Setting deadlines that ensure you reach milestones on time.
  • Focusing on one task at a time instead of multitasking.
  • Taking regular breaks to refresh your mind and body.
  • Learning to delegate work to other people on your team.

You can also access plenty of applications that can help you manage time more effectively. Top apps include:

  • Timely, which lets you compare your expectations with how long tasks actually take.
  • RescueTime, which tracks how you spend your time online so can spot websites that you might want to block while you work.
  • Workflow, which lets you execute a series of tasks with one tap.
  • Marinara Timer, which uses the Pomodoro Method to help you concentrate and plan breaks.

Final Thoughts

Soft skills don’t always seem important to people who work in high-tech fields. In reality, learning these skills will give you more opportunities to excel in your career. As a data engineer, there are a variety of ways to "soften" the workload- succeeding in these 6 soft skills, implementing a shadow IT into your system- we won't talk about that, and data software tools.

Xplenty is an ETL tool that will simplify the data integration process for your data team by transforming and loading your data to and from your data sources and destinations. Contact us to schedule a demo and risk-free trial.