Data engineering is a career that’s really picked up steam over the last few years. More companies are now making good use of the data they collect by handing it over to their Data Engineers, who format and organize it to prepare it for analysis. To do so, they create systems that allow for much smoother data analysis. Then, findings can be presented to leadership. Important business decisions are made based on their hard work.

What’s the difference between data engineering and data analysis?

Though they’re often lumped together into the same general career description, Data Engineers are a different group of professionals than Data Scientists or Data Analysts. In a sense, Data Engineers are the ones that pave the way for Data Scientists and Analysts because they’re responsible for creating the systems and maintaining the databases that store all the information.

When we sat down with Ryan, a Data Engineer from Warby Parker, he described his role as akin to a plumber:

“At Warby Parker, Data Engineers are responsible for creating and maintaining the plumbing required to support the data and reporting needs of the business. We use software engineering practices to automate the work of data cleaning, normalizing, and model building so that data is always ready to be consumed by Data Analysts in every department.”

What does a Data Engineer do?

Data Engineers are highly versatile pros. They can work within companies that haven’t yet established their data strategy or within data-dependent companies that have used data to guide their business for decades. That’s another highlight of a Data Engineer’s career. They can take their skills to any industry and apply them in new and exciting ways.

Some Data Engineers work on large teams, maintaining databases, cleaning data, and assisting Data Analysts with their technical issues or complicated tasks. Others spend their time teaching non-technical staff how to use databases to their advantage. Below, Ryan shares some of the exciting projects he’s been able to work on in his career:

“I’ve had the privilege of working with a lot of smart people in every department at our company to help them solve their varied data needs, from reconciling financial data with the Accounting team to automating and modeling standardized performance metrics for our team of over 200 customer experience advisors.”

As Ryan illustrates, Data Engineers play an integral role in a company as many departments rely on their skills, from accounting to marketing and design. Data Engineers use data to solve problems and make their colleagues’ jobs easier by implementing databases, training, and even automation.

What skills are required to become a Data Engineer?

Data Engineers are experts in SQL, which they use to manage their company’s databases. Many also have specialized knowledge in SQL’s associated frameworks, like PostgreSQL and SQLite, which further extend the language’s capabilities.

Data Engineers are specialized Software Engineers, so they need to understand how to program in at least one language, such as Python, JavaScript, or C++. Being able to code also enables Data Engineers to more easily manipulate and clean the data they work with every day.

Beyond their technical skills, Data Engineers also need to be meticulous and detail-oriented. To maintain a database or carefully clean datasets, they must be willing to get into the weeds and spend time on painstakingly precise work.

But, they also need to be big-picture problem-solvers as the systems they create allow Data Analysts and Scientists to query their databases and find business insights. So, there’s a balance between the two different types of thinking and working, which is great news if you love variety in your work and the ability to be technical but also creative.

How to become a Data Engineer

Data Engineers need to have the programming skills to create and maintain databases, and they need to know enough about the code their company uses to support Data Analysts and Data Scientists in their work. In all likelihood, this will be a different mix of languages and libraries for each company. So, the most important thing is to get the basics under your belt by learning at least one or two languages and practicing coding to solidify the concepts you learn.

The best news is that you can begin learning these languages and concepts right now. Online courses provide the framework you need to get familiar with the systems and tools you’ll need to become a Data Engineer.

First, you’ll want to learn SQL so you can understand how others will be querying databases you create. You’ll also want to learn Python as a general-purpose language and to complete our Design Databases with PostgreSQL Skill Path, which will teach you how to create your own databases.

If you’d prefer to learn everything you’ll need to know all at once, consider our Data Analyst Career Path. Not only will you learn how to use the languages and frameworks listed above, but we’ll also help you build a portfolio that’ll help illustrate your skills during your job search.

Don’t forget to enjoy the journey. Get involved in our online community when you’re learning a new language. By connecting with other learners, you’ll be able to talk the talk to prepare for when you land your next job in Data Engineering.

Data Engineering Courses & Tutorials | Codecademy
Data engineering is all about creating and maintaining the underlying systems that collect and report data. Without data engineering, the data that’s collected would be inconsistent and the information it tell us wouldn’t be particularly useful.

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