By creating and maintaining infrastructure that allows for efficient data collection, storage, and retrieval, data engineers can power everything from real-time analytics dashboards to machine learning models – all which help you make informed business decisions.
Although many data engineers are highly skilled, the current job market is a melting pot of fresh graduates, experienced professionals, and coding cowboys. In fact, finding a candidate with the right soft skills, personality, and technical abilities has become a bit of a minefield.
To get around this, you’ll need a robust and thoughtful hiring process to prevent making a catastrophic mis-hire, which can lead to poor data infrastructure, compromised data quality, and flawed business decisions.
In this article, we explore everything you need to know about hiring a data engineer, including where to find them, what skills to look for, and how to avoid common pitfalls.
Here are some of the most important things to consider before hiring a data engineer:
You need to determine exactly why you need a data engineer before beginning the hiring process. Consider upcoming data projects, your current data team’s knowledge gaps, and which specific challenges you need your new hire to solve. For example, if an upcoming project requires Apache Spark expertise, prioritizing candidates without this expertise would be counterproductive.
Not all data engineers are built the same. In fact, they have pretty diverse skill sets that reflect the wide range of tasks and responsibilities data engineering encompasses. As a result, it’s essential that you hire a data engineer whose skill set matches your business’s needs.
Although certifications give a great insight into a candidate’s technical ability, many data engineers are self-taught or attend uncertified boot camps to grow their skills. Don’t be put off by candidates who can’t produce the necessary qualifications, as they may be just as skilled as their certified counterparts. Instead, use pre-employment testing tools to measure applicants’ technical abilities and hire data engineers.
Talented data engineers are in high demand, and you need to be prepared to compensate them well for the skills you need. Data engineers often incur a hefty payroll price tag because of the competitive job market and their highly specialized skill set.
Consult industry salary surveys and research market rates to find information on compensating data engineers. For example, you can use sites like salary.com, which gets compensation data from employer reports, public data sources, and market surveys. Also, consider factors like experience level, skill set, geographic location, and the complexity of the role to offer a competitive package that attracts top talent.
Look for the following skills and qualifications in a data engineer:
Depending on the nature of your business, you may need a data engineer with the following skills:
Programming languages. Candidates should have strong technical ability in whatever programming language your business uses – for example, Python, Java, C++, or Scala.
Cloud programming. An understanding of cloud platforms like Google Cloud or Azure is crucial for data engineers. They should also have the ability to work with other cloud-based data services.
Data security. An understanding of data security best practices and the ability to comply with data privacy regulations will help candidates navigate the heavily regulated world of data engineering. In fact, in industries like health, government, and financial services, knowledge of data security is essential.
Scripting and automation. Proficiency in scripting for automation tasks and system administration will help candidates excel in data engineering roles.
Soft skills are needed to excel in any workplace. Look out for a candidate who shows:
Strong communication skills. Communication skills will help candidates build strong workplace relationships, work cross-functionally with other departments, and effectively convey technical concepts to non-technical colleagues.
Problem-solving abilities. Data engineers face complex problems every day. You need a candidate who thinks logically, can solve problems systematically, and keeps a level head.
Adaptability. Data engineering is an ever-changing field. Due to the speed and volume at which the modern world generates data, data processing must continually evolve. You’ll need a candidate who is adaptable to change and can pivot quickly to meet the demands of the business.
Attention to detail. A keen eye for detail will ensure your candidate corrects their mistakes and maintains accuracy. A candidate who doesn't have strong attention to detail could leave your business open to noncompliance and legal risks, missed opportunities, and reputational damage.
Finding skilled data engineers can be tricky. Try looking in the following locations:
Although you might be familiar with LinkedIn, a popular professional networking website, you should consider using less-popular platforms.
Stack Overflow Jobs is a popular online job board for programmers and data professionals. Posting a job there can help you reach skilled data engineers.
Datajobs.com is a lesser known but reputable online job platform that connects talented data professionals with new job opportunities.
Professional recruitment agencies specializing in tech and data roles can be game changers. These recruitment professionals have in-depth knowledge of data and engineering industries – in fact, some of them have pivoted from engineering and data into second careers. The downside: these agencies can be costly. But if you’re in a pinch, they can quickly put you in touch with data engineers who they believe are best suited to your business.
University or college careers centers can help you find newly qualified graduates to grow your business. These applicants will be looking for roles to support their growth.
Conferences, trade shows, or summits are another great way to meet new candidates. You may be able to set up recruitment booths to network with talent and hand out business cards. For example, check out DeveloperWeek or the Cassandra Summit.
Industry talks or presentations hosted by local tech organizations can provide excellent opportunities to connect and network with skilled data engineers.
Can’t find the right candidates through traditional recruitment methods? Try these three alternative ways to find data engineering candidates.
Twitter can be a great place to find data engineering candidates since you can network with all sorts of industry professionals, engage data engineers in discussions about current trends, and direct message engineers who might be interested in your position. You can also search for specific hashtags and profiles of people with expertise in data engineering.
GitHub is a treasure trove of projects and contributions, some created by data engineers. Search for contributors who are posting the kind of projects they’d undertake in your business. Reach out to them directly with any potential opportunities.
Reddit’s /dataengineering forum is a great platform to connect with data engineering professionals. Although you can’t specifically post about jobs there, you can connect with professionals and let them know you’re looking for new employees.
Upwork and Fiverr – other freelancer networks – are another great way to find data engineering candidates. These platforms are useful if you’re hiring for project-based roles or need an extra pair of hands for a task. However, you can also find permanent candidates or agencies through these platforms. Try opening a contract detailing exactly what kind of support you need, and see who reaches out.
Whether you post your job on forums or use other creative methods for seeking out data engineers, make sure you clearly describe the role to any interested parties so that only the best-fitting candidates apply for your position.
After finding interested applicants, it’s time to shift your focus to selecting the ones with the most promise. Follow these steps:
You should screen candidate resumes for achievements, technical skill level, certifications, and professionalism to weed out ill-fitting candidates. In today’s job market, over 80% of resumes are thrown out at the first screening. By quickly eliminating applicants who clearly aren’t good fits, you can greatly narrow down your candidate pool to focus on top candidates.
You can then ask the most-qualified candidates to complete pre-employment tests that will measure the skills they claim to have – including technical skills like coding language proficiency or soft skills like communication. These objective tests help you make data-driven decisions for selecting the best candidates based on merit.
Unsure where to start? Check out TestGorilla’s range of pre-employment tests for data engineers.
After further narrowing down your candidate pool, interview the best candidates. Design your interview questions to reflect the qualities you are looking for in a candidate. For example, to enhance your understanding of your candidates’ attention to detail, you should ask questions like, “How has your attention to detail made a significant difference in the outcome of a specific project?”
Be mindful of these common mistakes when recruiting for data engineers:
Real-world experience helps you measure whether a candidate has the practical skills and can apply their knowledge effectively. In fact, many skilled data engineers gained their knowledge through on-the job training as opposed to technical qualifications. Look for candidates who can evidence their ability to handle real-world engineering challenges through situation-based interview questions.
Don’t make the mistake of overlooking the impact of soft skills when hiring data engineers. Soft skills include problem solving abilities, communication skills, attention to detail, and collaboration. A well-rounded data engineer who possesses not only technical expertise but also strong soft skills can contribute significantly to the success of your business.
Take your time when hiring a data engineer. It’s better to invest the time in a thorough and thoughtful hiring process than rush and make a costly mis-hire. After all, your data engineer is responsible for your data, so make sure your data is in the right hands.
Data is the lifeblood of modern businesses, and data engineers are skilled professionals who keep this data accurate, secure, and understandable. By ensuring data quality and availability, they indirectly contribute to more accurate and timely business decisions.
However, hiring a data engineer can be tricky. With so many coding languages and skill sets to consider, you’ll need a robust process to ensure your next hire is the right fit for your team.
Luckily, TestGorilla can help. Using TestGorilla’s pre-employment testing tools, you can measure your candidates’ communication skills, technical abilities, and data handling proficiencies before inviting them to interview. This will streamline your recruitment process and ensure you pick the best candidate for the role – one who can enhance your decision-making.
To address its increased recruitment needs and influx of applicants for roles that include customer support and leadership, Dyninno Group implemented TestGorilla. See how the Dyninno Group of companies improved candidate screening and recruitment productivity by 400%.
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