How to assess data engineering skills

Data is everywhere. Organizations have long collected and used data to improve their strategies, products, and efficiency, but today they must store all this data somewhere fit for the modern world.

Data engineers are responsible for creating, managing, and optimizing digital software that can store large amounts of data. They play a vital role in today’s globalized world, giving companies the information and insights necessary to thrive.

Since they play such a pivotal role in the success of modern businesses, you should ensure any data engineers you hire have the right skill set to benefit your organization. Using TestGorilla’s talent assessments is the best way to do this.

Read this guide to discover what skills data engineers need to be successful and learn which assessments you can use to evaluate your candidates’ abilities.

What is a data engineering skills assessment?

The nature of data engineering requires a combination of hard and soft skills. Your candidates must demonstrate keen abilities in various skills, from coding to critical thinking, to carry out their duties effectively and successfully. This means you should use a data engineering skills assessment when hiring data engineers for your firm.

A data engineering skills assessment consists of various skills and traits tests designed to evaluate applicants’ abilities before the interview stage in the hiring process. The assessment may test specific technical competencies or broader interpersonal skills, including:

• Coding and computer programming

• Data analysis

• Knowledge of databases

• Data warehousing

• Machine learning

• Operating systems

• Communication

• Problem solving

• Broader analytical skills

The best way to use a data engineering skills assessment is to combine various tests to cover as many skills and traits as possible. For instance, you could use a short Scala proficiency test alongside a communication skills test to evaluate some of the crucial hard and soft skills required for successful data engineering.

With TestGorilla, you can include up to five skills tests in your assessment. Learn how in creating an assessment with TestGorilla.

Why are data engineer skills important?

Data engineers transform raw data into legible and understandable structures. They are responsible for building the structures that house data, often interpreting, manipulating, and analyzing the information along the way.

Here are three key reasons why data engineering skills are important, both for the individuals themselves and for your company as a whole:

1. Ensure business process quality

Adept data engineering skills can massively improve the quality of your business operations. For instance, a data engineer with comprehensive data analysis abilities can easily identify errors during troubleshooting and resolve them more quickly. This enhances the overall quality of your systems, processes, and end products.

Strong coding skills also help raise the quality of your company operations. Proficiencies in multiple coding languages will reduce the number of errors your data engineer makes in their work. It will also decrease the likelihood of malfunctions in your data structures, ensuring your overall business processes run smoothly and function effectively.

2. Enhance company efficiency

Data engineering skills also play a key role in enhancing company efficiency. A data engineer with strong communication skills can give instructions clearly and concisely, saving everyone time and confusion. They can also easily present technical information to non-specialists, reducing miscommunications and misunderstandings between departments.

Additionally, if your data engineer is proficient in multiple programming languages, they can quickly adapt to different tools and work across various platforms without extra training. This ability will enhance the efficiency of your business processes, as your new hire can switch between software effectively.

3. Make computer code understandable to non-specialists

Raw computer data is only useful with someone who is able to interpret it. Data engineers can manipulate and present data in a way that’s understandable to non-specialists. They can then send the information to other departments and senior figures for analysis and strategizing.

Crucially, other departments can use this now-legible data to leverage insights and implement new strategies. They can identify areas for improvement within your company and adjust business processes to reflect the data. Strong coding and analytical skills are essential for data engineers, as they help others in your company interpret vital data.

Which skills and traits are important for data engineers?

Data engineers need a combination of hard and soft skills to be successful in their roles. As a recruiter, you must look for candidates with broad and varied skill sets. This could include technical competencies like data analysis and coding but may also involve sourcing applicants with strong communication and problem-solving skills.

Your next data engineer should be able to demonstrate their abilities in various skills and traits. The following are key competencies that you should look out for in your candidates:

Data analysis

First and foremost, your data engineering candidates should possess knowledge of analytics software. Data analysis is a valuable skill that you should look for in your applicants because it allows them to interpret data and propose sensible strategies and solutions in the future. With strong data analysis skills, your candidates can drive profitability and growth.

The best data engineers can apply their knowledge of computer programming languages to perform comprehensive data analysis. For instance, your candidates may be proficient in data analysis using R or Python. Look for applicants with strong data analysis, communication, manipulation, testing, and presentation skills.

Coding and computer programming

Computer programming is a big part of a data engineer’s job role. Data engineers can only successfully fulfill their duties with significant coding skills and a deep understanding of programming principles. This involves a working knowledge of multiple programming languages, such as Python, Ruby, C++, Scala, Java, and Golang.

As a recruiter, you should use talent assessments to gauge your candidates’ coding abilities before you hire. Tailor your data engineering skills assessment to the tools and systems you use. For instance, if your company uses Ruby as the main programming language, test candidates on their Ruby coding skills.

Operating systems expertise

Another hard skill that successful data engineers should possess is a thorough knowledge of operating systems (OS). Linux, Microsoft Windows, Solaris, and Apple macOS are the most common operating systems, but it’s worth hiring candidates with proficiencies in the OS that your organization uses.

Different operating systems meet different requirements, so data engineers should have a broad understanding of various systems. For instance, Linux is excellent for handling large amounts of data, while server clusters are better managed using Microsoft Windows. You should look for candidates with skills in the OS that are relevant to your company.

Database knowledge

A data engineer frequently works with databases, so you must look for candidates with a solid understanding of database structures, systems, and management. Structured Query Language (SQL), Bigtable, and Cassandra are the most frequently used database solutions. If your company uses one of these, database knowledge is even more of a priority skill to look out for.

TestGorilla offers many SQL-related pre-employment tests. For instance, if your organization uses Microsoft SQL, it may be worth evaluating your candidates’ Microsoft SQL Server skills. Alternatively, you can use our SQL Server Management Studio test to assess applicants’ design, development, and management abilities.

Communication

Strong communication skills are vital in many professions, including data engineering. Data engineers rarely work alone, so they need effective verbal and written communication skills to convey correct information to their team members, colleagues, and superiors.

Many people that data engineers interact with will not have technical expertise in the field. As a result, data engineers need to communicate clearly and concisely to relay relevant information in terms non-specialists can understand.

That said, data engineers frequently interact with fellow specialists, such as data architects and data scientists. This means your candidates should have a strong understanding of technical terms and concepts to communicate effectively with their peers.

Critical thinking

Critical thinking skills are vital in the role of a data engineer. Typically, they are asked to find creative solutions that don’t exist yet, so they should possess strong critical thinking skills to develop new solutions.

These abilities are also valuable in troubleshooting. Data engineers are frequently required to test their company’s existing processes and structures to find errors. Resolving these inefficiencies, mistakes, or faults in an efficient manner requires a good deal of critical thinking. This way, data engineers can find clever solutions to improve your organization.

Skills and traits tests

Data engineering is a highly skilled profession. Traditionally, recruitment methods have relied on resumes and interviews to source talented data engineers. When you hire this way, you risk hiring underqualified and unskilled data engineers.

Skills-based hiring is the only way to effectively ensure your new employees possess the right abilities to fulfill their job expectations. Data engineers need many skills to succeed in their roles, so your candidates must prove their competencies before you hire them. To easily facilitate this, you can use talent assessments from TestGorilla.

Here are six skills and traits tests that you can use to hire the best data engineers for your organization:

Data Modeling Concepts

The nature of data engineering involves working with copious amounts of data. As a result, data engineers must know how to manipulate, model, and analyze data using various systems and software. Data modeling is one of the core concepts that every data engineer should know.

You can use our Data Modeling Concepts test to hire the most skilled data engineers for your company. This intermediate-level assessment covers the key principles of data modeling, including:

• Conceptualization

• Normalization

• Determining prerequisites

• Creating logical models

• Creating conceptual models

• Creating physical models

Your new hire should be able to apply data modeling concepts to structure data in a way that’s clear and easy to understand for other parties. The high-performing candidates on this test likely represent the best applicants for your open position, as data modeling is a key responsibility of a data engineer.

To further evaluate candidates’ skills, use our data modeling interview questions.

Database Management and Administration

Data engineers must also know how to manage and manipulate databases. Whatever database management system your company uses (such as SQL, Bigtable, or Cassandra), you must ensure your new data engineers understand the relevant database management protocols and principles.

Use our Database Management and Administration test to hire skilled data engineers for your organization. Test material covers database-related concepts, including security, data recovery, performance management, warehouse management, design reviews, and data availability. It’s a comprehensive test designed to source highly-skilled data engineers.

Linux

Linux is one of the most popular operating systems that data engineers use. If your organization uses Linux for everyday activities, it’s worth testing your candidates on their abilities to understand, manipulate, and implement Linux procedures.

Our Linux skills test will help you gauge applicants’ Linux proficiency levels. It’s a mid-level test that covers all the fundamentals and certain advanced features of Linux, including security and privacy protocols, Linux Systems Administration, Linux Internals, and the Linux Ecosystem.

High-performing candidates will be able to apply their knowledge of Linux to real-world scenarios successfully. They’ll solve simulated problems and demonstrate practical abilities in operating, managing, and coordinating Linux systems.

Apache Spark

Data engineers widely use Apache Spark, one of the most powerful data processing tools available. If you’re one of the countless organizations using Apache Spark, you must ensure your new hires are well-versed in the tool to avoid time-consuming and costly onboarding.

Start by writing a strong Apache-spark developer description. Then, use our Apache Spark for Data Engineers test to find skilled candidates trained in this programming framework. The assessment covers the fundamentals of Apache Spark, including data transformation and processing, Spark Core, Spark Streaming, and GraphX.

Candidates who score highly in this mid-to-senior–level test can streamline business processes and complete data projects more quickly. This will ensure your company can implement data-driven solutions and strategies more efficiently.

Python (coding)

Coding is one of the key skills that every data engineer needs. During the recruitment process, you should be on the lookout for candidates who demonstrate comprehensive abilities in multiple computer programming languages, especially the one your organization uses most.

Python is one of the most popular and widely used programming languages. If you’re one of the many companies that utilize Python in your day-to-day processes, you should consider evaluating your candidates' Python skills.

You can do this with our Python (coding): Data Structures and Objects test, an intermediate-level test that evaluates applicants’ object-oriented programming skills. You can assess candidates’ abilities to manipulate and implement data structures, allowing you to find skilled data engineers with strong Python competencies.

Problem Solving

A key responsibility of a data engineer includes identifying issues and proposing appropriate solutions. They must troubleshoot their processes, recognize errors in their work, and develop creative fixes for any problems. For this, data engineers require strong problem-solving skills.

Our Problem Solving test can help you assess candidates’ abilities to find clever solutions to real-world scenarios. The test evaluates applicants on skills related to interpreting data, applying logic to find solutions, creating and adjusting schedules, prioritization, establishing order, and analyzing textual and numerical information.

Data engineering skills assessment FAQs

Need more information on how to assess data engineering skills? Read our answers to the following frequently asked questions:

What are data engineering skills?

Successful data engineers require a range of hard and soft skills. They must blend interpersonal skills like communication and active listening with technical competencies like data analysis and computer programming. Problem solving, critical thinking, and an analytical mindset are all additional skills and traits that top data engineers should possess.

Do data engineers need coding skills?

Coding forms a significant part of a data engineer’s day-to-day duties. They may use programming languages to input, collate, manipulate, extract, and analyze data. Coding tools are also useful for building data structures and databases, so data engineers require at least a foundational knowledge of multiple programming languages, such as Python, SQL, and R.

Is data engineering a lot of math?

While math may not be a large part of a data engineer’s everyday duties, it occasionally crops up. Data engineers should have an intermediate level of math ability and understand core mathematical principles like calculus, statistics, probability, and algebra.

How TestGorilla can help you find skilled data engineers

Recruiting a data engineer can be a lengthy process, considering the responsibilities and expectations of the job. It’s especially difficult if you’re not familiar with the field of data engineering. This is where TestGorilla’s talent assessments can help. Here’s how:

• Tests backed by science. All our tests are designed by specialists in the subject matter and peer-reviewed by additional experts. Our overall approach to recruitment is also supported by science, so you can feel confident using our skills assessments.

• Remove bias. TestGorilla’s talent assessments provide bias-free hiring. You’ll get an objective list of the highest-scoring candidates, regardless of race, age, or gender, which you can use to recruit diverse team members without bias.

• Effective hiring. Our tests not only speed up your recruitment process but also improve your hire’s quality. You can quickly hire the best person for the job, reducing recruitment costs and increasing employee retention rates.

After you’ve evaluated your candidates’ data engineering skills, you can invite the best-performing few for interviews. Then, you can use our data engineer interview questions or Spark interview questions to expand your understanding of each applicant and narrow down the best person for the job.

Hire top data engineers with TestGorilla

Recruiting skilled data engineers can be difficult, but the process can be made easier with TestGorilla’s skills-based hiring method. Our skills and traits tests are supported by extensive research, easy to implement, and bias-free. Adding our talent assessments to your hiring process will improve your recruitment quality and speed.

If you’re looking to hire skilled data engineers for your organization, include a data engineering skills assessment in your recruitment. This modern approach will help you source the best individuals who can fit into your company with minimal effort.

Start your free TestGorilla plan today to discover the benefits of skills-based hiring.