The average salary for data engineers in the United States in 2024 is $129,049 (source: Indeed.com)
While this figure provides a broad snapshot, it doesn’t tell the full story. In reality, data engineer salaries vary significantly across different states, influenced by factors such as:
- local cost of living
- presence of tech hubs
- regional demand for skilled professionals
Even though remote work has blurred some of these geographic boundaries, location still plays a major role in determining pay.
For instance, states like California and Hawaii, where the tech industry is deeply integrated into the local economy, boast average salaries well above the national average, at $148,142 and $152,862, respectively.
At the high end of the spectrum, Montana and North Dakota surprisingly top the list with averages of $175,976 and $179,949, likely due to the scarcity of skilled talent in those areas, driving up demand and compensation.
In contrast, states like Louisiana and South Dakota offer much lower average salaries for data engineers, at $93,428 and $92,941, reflecting less demand or less developed tech industries.
These wide-ranging salary figures illustrate the ongoing importance of location in determining pay, despite the rise of remote work. While top salaries tend to cluster in states known for tech innovation or higher living costs, data engineers can still find competitive compensation across a variety of regions, depending on their skill sets and the industry they work in.
Average salary for Data Engineers by U.S. State
- Alabama: $133,644
- Alaska: $138,107
- Arizona: $119,948
- Arkansas: $103,200
- California: $148,142
- Colorado: $121,908
- Connecticut: $134,761
- Delaware: $132,684
- Florida: $114,003
- Georgia: $118,384
- Hawaii: $152,862
- Idaho: $130,214
- Illinois: $127,870
- Indiana: $131,586
- Iowa: $119,555
- Kansas: $140,991
- Kentucky: $102,155
- Louisiana: $93,428
- Maine: $147,774
- Maryland: $138,965
- Massachusetts: $129,112
- Michigan: $115,244
- Minnesota: $115,141
- Mississippi: $131,924
- Missouri: $117,909
- Montana: $175,976
- Nebraska: $121,315
- Nevada: $119,395
- New Hampshire: $166,827
- New Jersey: $126,191
- New Mexico: $132,771
- New York: $131,309
- North Carolina: $123,648
- North Dakota: $179,949
- Ohio: $108,708
- Oklahoma: $113,361
- Oregon: $125,555
- Pennsylvania: $120,928
- Rhode Island: $125,491
- South Carolina: $131,558
- South Dakota: $92,941
- Tennessee: $120,111
- Texas: $122,478
- Utah: $124,848
- Vermont: $148,327
- Virginia: $137,111
- Washington: $136,444
- West Virginia: $99,508
- Wisconsin: $126,832
- Wyoming: $110,533
Other factors that have an impact on the salary of data engineers
Several other factors influence the salary of a data engineer, ranging from industry and skills to experience and location. Here’s a breakdown of the most impactful elements.
Industry
• High-demand sectors like finance, healthcare, and AI pay significantly more due to their reliance on complex and secure data systems.
• Data-centric companies, such as tech giants, AI startups, and fintech firms, often offer premium salaries as data plays a crucial role in their business strategies.
Skills and specializations
• Data engineers with expertise in cloud platforms (AWS, Google Cloud, Azure), big data tools (Hadoop, Spark), or real-time analytics frameworks (Kafka, Flink) command higher salaries.
• Engineers with niche skills such as machine learning infrastructure or data architecture are in high demand, which can lead to salary premiums.
Experience
• Early-career data engineers experience rapid salary growth as they build their portfolios, with mid-level and senior roles offering six-figure salaries.
• Specialized senior engineers, particularly those working on complex distributed systems, tend to earn more than those in generalist roles.
Company size and stage
• Large tech companies and established enterprises often offer higher base salaries, while startups may offer competitive pay combined with equity and stock options.
• Engineers working at high-growth companies undergoing digital transformation often see more frequent salary increases and larger bonuses.
Certifications and education
• Certifications like AWS Certified Data Analytics or Google Cloud Professional Data Engineer can significantly boost salaries, demonstrating up-to-date expertise.
• Advanced degrees (e.g., in data science or engineering) can lead to higher pay, but many high-earning data engineers succeed without traditional degrees, focusing instead on hands-on experience and certifications.
Business impact
• Data engineers who can directly influence business outcomes—such as improving a company’s data strategy or driving cost-saving efficiencies—tend to earn more, especially in companies where data is a key revenue driver.
Negotiation and compensation packages
• Salary isn’t the only factor; stock options, bonuses, and other benefits (like remote work stipends or learning opportunities) can significantly raise total compensation.
• Engineers who are skilled at negotiating offers or leveraging multiple offers can often secure higher pay and better benefits.
These factors work together to shape what a data engineer can earn, with those who stay current on technology trends and understand their market value being best positioned to maximize their compensation.