How Much Do Data Engineers Make in the USA?

What Does a Data Engineer Do?

Data engineers can be found working in an eclectic sampling of settings, building systems that gather, manage, and transform raw data into usable, valuable information for data scientists and business analysts to interpret. Their goal is to make these enormous volumes of data accessible so that companies and organizations can then use it to evaluate and optimize performance.

Here are a few of the typical tasks data engineers perform:

• Gather data sets that align with their organization’s needs
• Build, test, and maintain data pipeline architecture
• Collaborate with management to understand company objectives
• Stay on top of new data analysis tools and data validation methods
• Develop algorithms that transform data into actionable insights
• Ensure compliance with the organization’s data governance and security policies

Large organizations typically have some data engineers dedicated to constructing data pipelines, while others are focused on managing data warehouses. Both populate warehouses with data and create table schemas that track the data's storage locations. On the other hand, smaller companies often expect their data engineers to assume a more generalist role, taking on a greater variety of data-related tasks.

What is the Average Data Engineer Salary in the USA?

So, what does an average data engineer salary in the USA look like? According to the Glassdoor job site, the annual median data engineer salary in the United States is $130,000. However, there are several factors to consider when discussing salaries, which we will examine next. 

Factors That Affect a Data Engineer Salary

Remember, the above data engineer salary figures represent averages, not considering any possible mitigating factors. So, what affects a data engineer salary in the USA? Salaries vary according to different parameters, such as the engineer's experience level, location, industry, company or organization, and the level of education and certification held by the applicant.

Let's take a deeper dive into United States IT data engineer salaries filtered through different factors.

Salaries by Experience Level

Here’s how Glassdoor breaks down data engineer salaries by experience level in the US.

Salaries by Geographical Location

As you browse through the various salaries using different filters, you will discover that there are many different combinations and factors that you can mix and match to find the set of circumstances that best describes you.

For example, let’s look at the figures of one job search site, ZipRecruiter. Here is what a data engineer salary looks like by U.S. city.

The Top-Paying Companies

According to Glassdoor.com, these are the current ten highest-paying companies for data engineers.

The Top-Paying Industries for Data Engineers

Additionally, Glassdoor reports that these are the top-paying industries for data engineers in the USA.

• Energy, Mining & Utilities: $140K/per year
• Agriculture: $139K/per year
• Financial Services: $137K/per year
• Media & Communication: $137K/ per year
• Hotels & Travel Accommodation: $135K/per year

What’s the Data Engineer Job Outlook?

But the question remains: what's the data engineering career outlook for 2025 and beyond? Research shows the profession is still a stable, rewarding career path. Some of the key trends: 

• Annual median salaries range from $98,000 to $131,000

• Cloud platforms like AWS and Azure are becoming increasingly popular, with AWS emerging as the most popular platform this year

• Programming skills remain necessary for successful data engineers—Python, SQL, and Java are the most sought-after languages

Also, employers are increasingly seeking out well-rounded data engineers, instead of hiring specialists. Many organizations want professionals who can seamlessly move between building data pipelines, managing cloud infrastructure, and creating visualizations. 

According to a StartUs report, the data engineering sector experienced a 22.89% industry growth and added over 20,000 new jobs in the past year, employing over 150,000 data engineering professionals.

Not confident about your data engineering skills? Join the Professional Certificate Program in Data Engineering, and master data pipelining, big data analytics, data visualization, and provisioning data storage services in just 7 months! 🎯

The Best Data Engineer Skills and Certifications

• Automation and scripting: Automation is an important part of working with big data because today's organizations collect vast quantities of information. Data engineers should be able to develop scripts to automate these repetitive tasks.
• Big data tools: Data engineers are often tasked with managing big data in addition to working with regular data. Popular tools include Hadoop, Kafka, Spark, and MongoDB.
• Cloud computing: As companies increasingly move from physical servers to cloud services, data engineers must be proficient in cloud storage and cloud computing.
• Coding: This role requires proficiency in programming languages, including Java, SQL, NoSQL, Python, R, and Scala.
• Data security: Although some organizations have dedicated data security teams, data engineers are often responsible for securely managing and storing data.
• Data storage: Not all data types can be stored the same way, especially big data. For instance, data engineers who design data solutions for their organization should know when to use a data lake instead of a data warehouse.
• ETL systems: ETL (extract, transform, and load) is the process by which data moves from databases and other sources into one repository, such as a data warehouse. Standard ETL tools include Alooma, Stitch, Talend, and Xplenty.
• Machine learning: Although machine learning lies more in the province of data scientists, it can still be wise to know its basic concepts better to understand the team's data scientists' needs. 
• Relational and non-relational databases: Databases are one of the most common data storage solutions. Thus, data engineers should be familiar with both relational and non-relational databases and how they function.

Certifications can validate data engineer skills to potential employers. Preparing for a certification exam is an ideal way to develop these valuable skills and knowledge. Certification options include:

• Associate Big Data Engineer
• Cloudera Certified Professional Data Engineer
• AWS Certified Data Analytics
• Microsoft Azure Data Engineer Associate
• IBM Certified Data Engineer
• Google Cloud Certified Professional Data Engineer

Do You Want to Become a Data Engineer?

The high demand for data engineers makes it an excellent career choice, whether you’re just starting off in the workforce or you’re already employed but looking for an upgrade. So why not start things off right with this Professional Certificate in Data Engineering online course?

This seven-month course is ideal for professionals and equips the learner with the fundamentals of Big Data, Python, SQL, NoSQL, Snowflake, AWS, Azure, and GCP. It includes over 150 hours of core curriculum, live sessions covering the latest AI trends, numerous case studies, and over a dozen projects.

Earn your data engineering certificate and prepare to experience an exciting, highly demanded professional career. 

FAQs

1. Where in the USA can a data engineer earn more?

Judging by the salary data provided by ZipRecruiter regarding data engineer salaries in top cities, California and Alaska appear to have cornered the market on high-paying data engineering jobs. However, any state that has dedicated zones of high-tech companies tends to pay more than the average data engineer salary.

2. What is the highest pay for data engineers in the US?

The highest pay for data engineers in the US can be as high as $300,000 or even higher, according to Glassdoor. These high salaries are typically paid to high-level data engineer positions, such as senior or lead engineers.

3. How can data engineers in the US increase their salaries?

Data engineers in the United States can increase their salaries by:

• Increasing/enhancing relevant data engineering skills
• Acquiring appropriate certifications
• Acquiring practical experience via real-world projects
• Getting promoted
• Networking
• Effective salary negotiations
• Signing on with a larger company, since big companies tend to pay more

Note that many of the above are interrelated.

4. How does a data engineer salary compare to other tech roles?

Data engineer salaries compare favorably with those of other IT professionals, typically keeping up with, if not exceeding, their counterparts. For example, Indeed reports that data engineers typically earn more than data scientists. This point illustrates the strength of the data engineering position and its growing demand in the IT sector.

5. How does the cost of living affect data engineer salaries in the United States?

High costs of living typically cause organizations to offer greater salaries to data engineers. The high costs of living in states such as California and Alaska are reflected in the above-mentioned city salary figures, for instance.

6. What is the average salary for data engineers in the AI sector?

AI data engineers can earn a yearly median salary of $137,000, according to Glassdoor. Of course, this figure, much like the salary figures for standard data engineers, can vary depending on the size of the company, location, and experience level.