Want to Get a Data Engineering Job? Learn SQL!

So, you want to be a data engineer, but you don't know how to get there. In this article, we’ll help you understand the skills you'll need for different types of data engineering jobs. You’ll also find some data confirming that data engineer jobs are a good career choice.

Data engineering and various types of data engineer jobs have become very popular in recent years. And for good reason: Next to data science, data engineering is one of the fastest-growing branches of IT. The market simply needs experts who can deal with databases.

If you are ready to start learning SQL and join the elite group of data engineers, I recommend our Creating Database Structure track. It’s a set of 5 awesome interactive SQL courses that teach you how to create and manage tables, views, and indexes in popular relational database management systems like MySQL, SQL Server, Oracle, and PostgreSQL.

But maybe you need more reasons to decide if it’s worth becoming a data engineer. In that case, read on. First of all, you should understand what data engineering specialists do.

Who Is a Data Engineer?

Data engineers focus on the development and analysis of large-scale data collections, storage, and infrastructure. Those things are relevant in virtually every industry. Companies can collect vast volumes of data only if they have the people and tools to clean and organize it.

In a nutshell, data engineers are technically savvy professionals that serve as a bridge between software/app developers and more traditional data science roles. They function as the backbone of every business, establishing best practices for data collection, archiving, analysis, and administration. They manage the architecture, construction, and maintenance of database structures and data processing systems.

The work of data engineers makes research, modeling, and the development of machine learning models easier, safer, and more effective. More information about data engineers can be found in our article Who Is a Data Engineer?.

What Do Data Engineers Do?

The general responsibilities of data engineers vary greatly across industries and companies. Data engineers with a broad skill set typically work in smaller teams with data science specialists and analysts.

Even in the most developed and data-driven organizations, where everyone knows how to analyze and process data, someone is needed to organize it all and ensure that everything works smoothly. Thus, data engineers must have a good knowledge of the database language, which is usually SQL.

Some of the world’s largest corporations hire data engineers whose primary responsibility is to build and populate analytics databases. These are usually massive databases and data warehouses (which can span multiple databases).

Pipeline data engineers typically work for larger or medium-sized businesses. The responsibility for data interpretation and application is then typically shared among the data scientists. To learn more about what data engineers do every day, check out this YouTube video:

Branches of Data Engineering

Data engineering is a broad field with many subfields, allowing for numerous career paths. Maybe you’re an analytical person who prefers the analytical side of data engineering. Or maybe you prefer the development/coding side. Whatever the case may be, the field of data engineering offers numerous opportunities.

We‘ll divide it into the following categories:

1. Analytical Engineer

An analytical engineer uses programming languages (such as Java, R, and Python) relational database management systems (DBMSs) and SQL to gain a deeper understanding of the data and integrate disparate data processing systems. Analytical engineers actively seek ways to improve existing processes and how they are currently carried out.

2. Database Administrator

Database administrators collect data and test, build, and manage the systems that store it. Along with getting the data structures up and running, they test and tweak these systems to make them run smoothly and securely. Database engineers are in charge of ensuring the integrity and security of all collected data.

3. Data Architect/Builder

Data pipeline infrastructure development is the responsibility of data architects and builders, who design the systems that other data professionals in the company will use. They create procedures for gathering information from various sources, including apps, the Cloud, streaming, and social media platforms.

Data Engineers vs. Data Scientists: What’s the Difference?

Because engineering is a scientific discipline and engineers are a subset of scientists, it is easy to confuse data engineers and data scientists. However, a data scientist’s role differs significantly from that of a data engineer.

Remember, a data engineer is in charge of establishing the infrastructure required for large-scale data analysis. They are the architects who create the infrastructure that data scientists rely on. Data scientists often work directly with customers, whereas data engineers typically work behind the scenes.

Data scientists are primarily concerned with analyzing and interpreting the data. They must be knowledgeable about machine learning and data analytics, whereas data engineers must know data design and architecture. If you've just thought you'd like to become a data scientist, here's how to do it.

The data engineer is like the designer of a Formula 1 race car, and the data scientist is like a professional race car driver. They employ different methods, but they ultimately collaborate to achieve the same goals. A more in-depth examination of the distinction can be found in our article Data Analyst vs. Data Engineer: A Full Comparison.

Data Engineering Careers

The demand for data engineers will continue as long as data is processed. Because “data is the new gold”, the volume of data being created shows no signs of slowing.  According to the DICE 2020 Tech Job Report, data engineering was the fastest growing tech job in 2020. It also had the most significant year-on-year growth of all tech occupations.

Source: DICE Tech Job Report

Data engineering has also been dubbed one of LinkedIn's hottest careers in 2022. And the demand for this position is expected to rise further. Glassdoor estimates the average salary for a US-based data engineer is $111,431; Indeed lists an average of $118,897. It’s easy to see why this is such an appealing position.

Source: Glassdoor

Don’t know where to begin your data engineer job search? We’ve found the Top 10 Websites That Will Help You Find the Perfect SQL Job to help you find your dream data engineering job.

What Skills Do You Need to Become a Data Engineer?

To develop scalable data engineering solutions, you will need computer skills and problem-solving abilities

SQL is a must-have tool in the data engineer’s toolbox. Companies of all sizes –  from tech giants like Apple to small startups – require SQL proficiency in their data engineers. Because data is constantly moving, data engineers must be regular database users.

According to a market analysis of top tech companies like Meta, Amazon, and Google, the technical skills required for becoming a data engineer include SQL, Python, and Java. The top three soft skills are communication, management, and willingness to continually learn.

Mastering the fundamentals of SQL is a prerequisite for becoming a data engineer; the good news is that it is not as difficult as you might think. Our article Is It Difficult to Learn SQL? will explain why. If you’re new to SQL, you can begin your learning adventure with one of our interactive online courses:

• Complete beginners with no prior programming or IT experience should take our SQL Basics
• Intermediate users who want to refresh or deepen their SQL knowledge can take our SQL Practice
• Seasoned IT professionals looking to expand their SQL toolkit should check out our Advanced SQL

Our article on The Best Books for Data Engineers can also help you choose reading material that will further your goals.

The Path to Becoming a Data Engineer

Because data engineering is such a broad multidisciplinary field, universities do not offer degrees in it. Data engineers typically have a background in software engineering, mathematics, or business. Since data engineering is a specialized field, experience and expertise frequently trump formal training and education.

As a first step towards a career in data engineering, you should learn the basics of Cloud computing, programming, and database architecture. More information can be found in our article New Data Engineering Learning Path.

Certification can demonstrate to potential employers that you possess the necessary skills. Studying for the exam required to earn that certification is a fantastic way to expand your knowledge. Associate Big Data Architect, IBM Certified Data Architect, and Google Cloud Professional Data Engineer are all viable options. Hackr.io has analyzed the pros and cons of different SQL certification providers - check which one matches your goals most.

To really stand out from the crowd, you must begin working on your portfolio; a good portfolio will demonstrate your abilities to hiring managers and potential employers. Data engineering projects completed for class or on your own time can be displayed on a personal portfolio webpage.

Many data engineers begin in lower-level positions (such as business intelligence analyst or database administrator) and work their way up. As your knowledge and skill set grow, you will be able to take on more challenging tasks.

Ready to Launch Your Data Engineering Career?
As we’ve seen, data engineering is an undeniably appealing career path. Learning critical skills like SQL and developing your portfolio will put you on the fast track to becoming a data engineer. So why not start learning SQL today?

What to do:

• Sign up for a free account or log in to LearnSQL.com
• Choose a course from our offer. They all offer the first few exercises for free so you can see if you like our platform and the way we teach SQL.
• Finish your course and build your knowledge.
• Start looking for a new job!

We will help you achieve your data engineering goals!