Data engineers are in high demand—and companies are willing to pay over 125k for skilled workers

Data-related jobs are among the fastest growing of any occupation in the U.S., and they often come with six-figure salaries. However, it can be confusing to navigate through the data science education space due to there being a web of titles in the space, including data scientist, data analyst, data architect, and data engineer.

Data engineer positions in particular are hot, with year-to-year growth at a rate of over 30%, according to data from LinkedIn’s Emerging Jobs Report.

And if you don’t believe the data, just conduct a simple job search on the platform. Companies that are hiring data engineers at the time of this article’s publication include Instagram, Microsoft, Adobe, The Walt Disney Company, IBM, Wellsfargo, American Express, Rockstar Games, Fifa, Boeing, Netflix—just to name a few. 

What is a data engineer?

A data engineer focuses on developing, testing, and maintaining data infrastructure. Data engineers work with data pipelines and databases to power a company’s data team, in which they are a key part of. They do the foundational work that allows data scientists and data analysts to organize, decipher, and visualize data.  

How is a data scientist different from a data engineer?

While a data engineer focuses on doing the “legwork,” in terms of creating the processes for data collection and storage, data scientists are in charge of cleaning, analyzing, and using data to solve business programs, says the University of Virginia. 

In terms of jobs, the skills needed to excel in either position will likely be very similar; employers are looking for those who are experts in computer languages like Python and SQL. UVA says no matter which job title you are eager to pursue, obtaining a master’s in data science will enable you to have the necessary skills to succeed due to the degree’s versatile curriculum.

How much can data engineers make?

The average salary of a data engineer is typically between $120,000 and $130,000, according to estimates by Glassdoor, Indeed, and Salary.com. However, a data engineer’s pay ultimately will depend on several factors, namely education, experience, and location. 

Those with an advanced degree in a data field, for example, may earn more—as well as those with more professional experience, who may reach senior or lead data engineer positions. Moreover, those living in states like California or New York, where cost of living is higher, may receive a larger salary to account for expenses.

5 companies hiring data engineers—with high-paying salaries

Note: Data is based on job postings from July 2024; these positions may have since expired or changed.

What skills are helpful in data engineering?

AI skills in particular are in very high demand, according to Art Zeile, CEO of Dice. He points to consulting, finance, and consumer product companies, which are hiring “armies of AI professionals.” Capital One, as one example, has “thousands” of job openings in data science and data engineering, he says.

“If you’re not doing AI, and your competitors are implementing AI meaningfully in their business, then you’re just going to be less relevant,” Zeile notes.

Due to the logic of supply and demand, he explains that companies will dish out higher salaries seeking candidates with in-demand skills, like those needed for data engineering. Those with AI-related skills may get a salary boost of $20,000 as compared to those without, he adds.

In terms of learning, a master’s degree isn’t necessarily required to succeed in data engineering— it can be helpful. At a minimum, candidates must be experienced in Python.

Frequently asked questions

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