Data Engineer Salary in USA: 2024

The role of a Data Engineer is rapidly gaining recognition in the fields of science and technology. In the United States alone, the demand is soaring, with projections of 284,100 new data engineering jobs expected over the next decade. Currently, more than 10,573 data engineers are employed across the country, and their salaries have seen a notable 10% rise in the past five years, highlighting the growing value of this career.

What Does a Data Engineer Do?

The process of creating and developing systems for mass data collection, storage, and analysis is known as data engineering. It is a broad field that has applications in nearly every sector of the economy. Therefore, Data Engineers are responsible for building, maintaining, or developing systems that can collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret.

Their ultimate goal is to make data accessible so that organizations and enterprises can use it to evaluate and optimize their performance. Some of the responsibilities of a Data Engineer also include:

• Building, designing, testing, and maintaining data architectures as well as complex data pipelines.
• Ensuring compliance with data governance and security policies.
• Collaborating with management to understand company objectives.

How Much Do Data Engineers Make in the US?

In the United States, the average data engineer salary is $127,668, which roughly translates to an hourly rate of $55. However, various factors can influence this figure, including years of experience, location, education, and the company you work for:

• Experience is a crucial factor in determining a Data Engineer’s salary. Those with more years of relevant work experience typically command higher pay. The average compensation for an entry-level data engineer with one to three years of experience is $80,187. Conversely, a senior-level data engineer with eight years or more of experience makes $141,575 on an average.
• Geographic location significantly affects salaries. For example, in major tech hubs like San Francisco, data engineers can earn upwards of $157,309, reflecting the high cost of living and competition for talent. Other cities like Chicago ($131,172) also offer competitive salaries. Conversely, locations with lower costs of living may offer lower salaries.
• The size and type of company can also impact earnings. Larger companies such as IBM or Google typically offer higher salaries due to their extensive resources and need for skilled professionals.
• Education is another critical factor influencing salary potential. Most positions require at least a bachelor’s degree in computer science or a related field. Advanced degrees or specialized certifications (such as those from Google or AWS) can further enhance earning potential by qualifying individuals for senior roles more quickly.

Demand for Data Engineers in the USA

Data engineering positions are among the IT industry job categories with the quickest rate of growth, according to recent reports. Data engineers’ employment is expected to expand by 36% between 2023 and 2033, according to U.S. Bureau of Labor Statistics projections, which is much faster than the average for all occupations.

About 20,800 openings for data scientists are projected each year, on average, over the decade. There are 303,105 active data engineer job openings in the US. The need for businesses to efficiently use the growing amount of data that is produced every day is what is driving this expansion.

As data engineers are crucial in creating and maintaining data pipelines that facilitate efficient access to clean and reliable data, companies like Amazon, Capital One, and Accenture have reported high demand for data engineers as they seek to implement large-scale data initiatives. To meet industry demands, aspiring data engineers are required to possess a diverse skill set that includes:

• Proficiency in programming languages such as Python and SQL
• Experience with cloud services (e.g., Microsoft Azure)
• Familiarity with big data technologies like Apache Spark and Hadoop
• Understanding ETL (Extract, Transform, Load) processes, essential for integrating various data sources into cohesive systems.

Data Engineer Salaries by Their Roles

• Entry-level or Junior data engineer: An entry-level or junior data engineer typically has 0-3 years of experience and is often responsible for supporting senior engineers with data pipeline development, maintenance, and basic data management tasks. According to recent salary data, a junior data engineer can expect to earn an average salary of around $80,107 annually. This entry-level position serves as a stepping stone into more advanced roles.
• Mid-level or Standard data engineer: As professionals gain experience, they transition into standard data engineer roles, usually with 2-4 years of experience. In this capacity, they take on more complex responsibilities such as designing and implementing scalable data architecture. The average salary for a standard data engineer is approximately $114,069 per year. This role requires a solid understanding of programming languages like Python and SQL, along with cloud computing skills in Azure or AWS.
• Senior or big data engineer: Senior data engineers have significant experience (usually 5-8+ years) and are responsible for leading projects, mentoring junior staff, and making architectural decisions regarding data systems. They are highly skilled in managing large datasets and optimizing performance across various platforms. The average annual salary for a senior data engineer is around $141,575. This role often requires expertise in cloud services like AWS or Azure.

Conclusion

The demand for data engineers in the USA is robust and continues to grow rapidly, driven by an increasing reliance on big data analytics across industries. VeriiPro can help you find the most lucrative career opportunities within this rapidly growing field. We ensure that you find the best role for you and your goals. Get hired today!