As businesses create more data and increasingly rely on it to improve processes, the data engineering field is rising to the occasion. Every digital process — from advertising to recruiting talent to the sales funnel — creates more valuable data. Businesses need Data Engineers to help analyze it.

On average, Data Engineers make about $126,635 per year in the U.S., not including an average bonus of $5,000 per year or common benefits like commuter assistance, stock options, and unlimited time off. Still, their salary expectations vary depending on their location and employer. Below, we’ll explore how various factors can influence a Data Engineer’s salary.

How much do Data Engineers make on the East Coast?

The East Coast offers some of the highest salaries in the United States for Data Engineers. With the bustling business centers dotting the right side of the country, these higher figures come as no surprise.

For example, the average salary for a Data Engineer in New York City is $145,132 per year, and in Boston, you’re still above the national average at $129,952.

As you head south, the salaries dip a bit yet still stay north of six figures. In the D.C. area, for instance, Data Engineers make an average of $118,918 a year.

Here are some other East coast Data Engineer salaries:

  • South Carolina: $142,993
  • Miami Beach: $106,893
  • North Carolina: $103,604

How much do Data Engineers make on the West Coast?

Data Engineers also bring in above-average salaries in many West Coast locations, and, in some cases, the figures come in higher than those for their East Coast counterparts. For example, Data Engineers in Los Angeles earn $147,907 a year, on average, and the number jumps up to $163,684 a year in San Francisco.

Farther north, in Washington, Data Engineers earn an average of $134,809, despite having fewer computer giants like Google and Facebook in the area.

Some other salaries for Data Engineers on the West Coast include:

  • Oregon: $125,641
  • Alaska: $117,793
  • Long Beach: $114,779

How much do Data Engineers make in the middle states?

Data Engineer salaries remain competitive even in the middle states of the U.S., despite their lower living expenses. For instance, Data Engineers earn $101,886 per year in Kansas, and in Oklahoma City, the salary approaches the national average at $121,562.

The numbers remain high in Chicago, where Data Engineers make an average of $119,828 each year. Data Engineers in the middle states also get bonuses amounting to an average of $5,000, making their actual pay significantly higher.

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How much do salaries differ depending on the company a Data Engineer works for?

Along with your location, another of the biggest factors impacting your pay as a Data Engineer is the company you work for. The range of responsibilities — and the value you bring to the organization — will vary from one company to another, but a look at some of the Data Engineer salaries from major organizations sheds some light on what you can expect.

eBay: $178,954

eBay, the king of online auctions, pays Data Engineers far more than most other companies at $178.954. An online auction’s data collection and analysis play a crucial role in developing and managing its business model. Everything from customer buying habits to time spent on the site after adding items to shopping carts can be tracked and used to produce actionable data.

Finding the insights necessary to make companies like eBay succeed requires a solid understanding of data analytics. With our Data Analyst Career Path, you can learn SQL and Python, enabling you to build the solutions needed to make data-based decisions.

Facebook: $177,988

Facebook’s data engineering is central to its operation as a leading social media and advertising organization. As a result, they pay their Data Engineers $177,988 a year. At Facebook, data regarding the likes and dislikes of members and that of their friends can be collected and used to help position ads in the right locations.

Facebook also manages other apps, such as WhatsApp, where data collection can improve processes such as measuring call and videoconferencing quality. Data points related to these and other metrics can be correlated according to the area, time of day, or even using year-over-year statistical comparison.

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U.S. Cellular: $218,279

U.S. Cellular’s high pay rate of $218,279 per year may be due, in part, to the critical role data plays for telecommunications companies. Ensuring customers get the bandwidth and reception they need can only be achieved through data engineering.

Much of the telecommunications industry is powered by data. A company like U.S. Cellular may call upon a Data Engineer to gather information on cell usage in a particular location to help determine whether an investment in a new tower would pay off.

Data Engineers also design and maintain the databases and systems that cellular networks (and internet services) run on. Employees’ sense of achievement at U.S. Cellular is higher than average, with 71% of workers saying they feel they’re meeting their goals. This could also help explain the higher salaries.

Procter and Gamble: $149,082

There’s a good chance you have at least a few Procter and Gamble products in your home, and the prevalence of their products may account for their impressive Data Engineer salary of $149,082. Data regarding the sales and distribution of P&G’s soaps, tissues, air fresheners, batteries, oral care accessories, and more surely plays a central role in research and development, marketing, and more.

The future looks promising for Data Engineers

Data engineering is on the rise. One report says that the industry is growing at a rate of more than 50% every year. If you’re interested in becoming a Data Engineer, our courses are a great place to start. You can learn everything you need to flourish in the industry while building a powerful portfolio in our Data Scientist Career Path.

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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