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Data Engineer Salary in USA: How Much Can You Make in 2024?
Updated on 25 October, 2024
8.71K+ views
• 13 min read
Table of Contents
- What Does a Data Engineer Do?
- How Much Do Data Engineers Make in the US?
- Demand for Data Engineers in the USA
- Data Engineer Salaries by Role in the US
- Data Engineer Salaries by Industry in the US
- Data Engineer Salaries by Experience in the US
- Data Engineer Salaries by Education in the USA
- How to Boost Your Data Engineer Salary?
- Top Paying Industries for Data Engineers in the US
- What are the Data Engineer Salaries in Top Companies in the US?
- Top Paying Cities for Data Engineers in the US
- Conclusion
Demand for data engineers is at a peak today globally due to the massive amount of data that companies accumulate and work with this data to draw actionable insights and make better business decisions. To do that, the generated data must be interpreted to be understood by the end user. That's where the data engineer comes into the picture, making it a demanding profession today. Currently, 6,500 LinkedIn users identify as data engineers. Talking specifically about the USA, there are 6,600 job advertisements for this title in San Francisco alone. A fundamental shift has occurred, turning IT firms into data corporations and creating demand for data skills. Uber, Airbnb, Spotify, and other companies that provide data products are vying for the talent needed to create and operate data systems, vying for data engineers! As per Stitch, 50% of the world's data engineers are located in the United States, making the continent an excellent place for data engineers.
Data engineer salary in US attracts a pretty decent amount. On average, a data engineer in USA earns over $1,14,435. This blog helps you understand more about the data engineer salary in US.
What Does a Data Engineer Do?
Data Engineers are responsible for creating and maintaining an analytics framework. In addition, data engineers create data procedures. One of the prime responsibilities of a data engineer is to develop, maintain and operate databases and processing systems.
Using data, a typical data engineer helps machines to perform their duties. Data scientists and data engineers work reciprocally. Data engineer gathers and collects answers to appropriate questions gathered by data scientists. Moreover, the data engineer further stores and processes the answers. Achieving a Data Engineer Certification demonstrates a deep understanding of these processes and skills.
How Much Do Data Engineers Make in the US?
Let's look at data engineer salaries in US.
Duration | Average | Lowest | Highest |
---|---|---|---|
Monthly (sourced from indeed.com) | $9,473 | $5,873 | $15,280 |
Monthly (sourced from glassdoor.com) | $9,378 | $6,912 | $17,985 |
Yearly (indeed.com) | $1,33,798 | $72,000 | $1,77,000 |
Yearly (glassdoor.com) | $112,530 | $82,950 | $2,15,816 |
Hourly in freelancing | $63 | $50 | $75 |
Data engineer salary in the US per month may vary depending on skill level, qualifications, locations, and company employment.
Demand for Data Engineers in the USA
The demand for Data Engineers isn't limited to the USA. It is rising on a global level. However, when it comes to the best lucrative career, the USA is the preferred location. Therefore we will stick to demand in the USA.
After the inception of databases like Hadoop and NoSQL, there's a constant rise in the requirement for processing unstructured or semi-structured data. Data Engineers are responsible for these tasks.
Organizations with a team of data scientists are employing data engineers rapidly because data engineers are known to solve real-world issues efficiently and quickly.
Despite data science is being a thing of the essence, the world is adapting to use operational data where the end user can perform their analytics. Data Engineers help in this area by enabling integrated data structures and pipelines.
To summarize, with the constantly evolving various data types processes and ways to process data, the demand for Data Engineers will go on increasing shortly.
Data Engineer Salaries by Role in the US
Data Engineer salary in US varies as per the role. Let's have a look. Along with other roles, the average salary of a big data engineer in US is also included.
Role | Data engineer salary US per year |
---|---|
Data Engineer | $1,14,501 |
Sr. Data Engineer | $1,40,687 |
Lead Data Engineer | $1,40,971 |
Source: glassdoor.com
Role | Salary per year |
---|---|
Data Engineer | $1,15,00 to $,50,000 |
Sr. Data Engineer | $1,50,00 to $1,58,000 |
Source: builtin.com
Role | Salary per year |
---|---|
Cloud Data Engineer | $1,16,497 |
AI Engineer | $1,26,774 |
Lead Data Engineer | $1,40,971 |
Big Data Engineer | $1,16,675 |
Data Science Engineer | $1,27,966 |
Database Architect | $1,43,601 |
Enterprise Data Architect | $1,72,872 |
Hadoop Engineer | $1,43,322 |
Information Systems Engineer | $92,340 |
Machine Learning Engineer | $1,29,932 |
Data Architect | $1,27,398 |
Data Engineer Salaries by Industry in the US
Data engineer salary in US may vary as per the industry/sector. Let's look at a few prominent sectors appointing data engineers. It lists the average salary of a data engineer in US.
1. Tech
The list of Tech companies in the USA is impressive. Herewith are the top 10 tech companies in the USA.
Company name | Salary per year |
---|---|
Apple | $75,000 - $2,21,113 |
Alphabet | $2,01,005 |
CISCO | $182,617 |
Dell | $1,72,615 |
Intel | $1,05,683 |
IBM | $1,11,780 |
HP | $1,26,263 |
Microsoft | $1,83,785 |
Meta | $35,294 - $2,79,252 |
Tesla | $135,627 |
2. Healthcare
Let's look at the Healthcare sector, depicting data engineers average salary US.
Company name | Salary per year |
---|---|
Aetna | $1,08,202 |
AmerisourceBergen | $1,11,108 |
Anthem | $94,140 |
Cardinal Health | $1,25,339 |
Express Scripts Holdings | $1,22,309 |
Johnson and Johnson | $1,32,785 |
McKesson | $1,34,406 |
United Health Group | $1,07,363 |
Pfizer | $1,21,529 |
Walgreens Boots Alliance | $1,15,000 |
3. Government
Department/Category | Salary per year |
---|---|
Federal | $117,032 – $126,963 |
Municipal Corporations | $77,045 – $106,036 |
4. Finance
Herewith is the list of the top 10 finance companies in the USA, displaying data engineer salary in America.
Company name | Salary per year |
---|---|
American Express | $1,39,897 |
Bank of America | $1,22,301 |
Berkshire Hathaway | $1,55,944 - $1,67,487 |
Citigroup | $1,15,101 |
Freddie Mac | $1,33,333 |
Goldman Sachs | $1,38,472 |
JPMorgan Chase | $1,26,199 |
MetLife | $88,363 |
U.S. Bank | $1,09,675 |
Wells Fargo | $1,15,122 |
Data Engineer Salaries by Experience in the US
Pay scale based on experience is the typical norm. So does it apply to data science engineer salary in US. Let's look at data engineer salary in US for freshers and experienced as well.
1. Entry-Level Data Engineer Salary
Data Engineers having zero to one year of experience fall into this category. The designation is generally Junior Data Engineer. As per industry data, an entry-level data engineer US salary is $102,341 to $146,751. Glassdoor.com estimates the amount as $119,670 for the data engineer average salary in US.
2. Mid-Level Data Engineer Salary
Data Engineers experienced within 3 to 7 years of experience fall into this category. As per builtin.com, the average data engineer salary in US in this category is $150,581.
3. Senior Data Engineer Salary US
Data Engineers with more than 6 years of experience as Senior Data Engineers. The salary of data engineer in USA is $140,661 and can go up to $200,000 per year, as per Glassdoor.
Data Engineer Salaries by Education in the USA
Academic qualifications play a crucial role in the salary of data engineers in US. The following information helps to understand how much a US data engineer salary can be, based on the qualifications. Let's look at data engineer salary United States with no degree or having a bachelor's or master's.
1. No Degree
Candidates with excellent programming skills often skip the degree part and concentrate on pursuing a software development course. With regular Bootcamp sessions and working on real-time live projects, they emerge as excellent programmers and able Data Engineers. The average salary for data engineers having no degree earn around $77,000 per year.
2. Bachelors
Bachelor of Data Engineers graduate in Software Engineering, Computer Sciences, Maths, Statistics, or relevant disciplines. However, they must acquire data engineering skills to become Data Engineers. It can be either by pursuing a course with Bootcamp programs or self-learning.
Having a degree widens your scope of getting employment, as most organizations want their employees with basic graduations. The mean salary for a Data Engineer with a bachelor's degree is $97,466.
3. Masters
Holding a Master's degree is a great advantage. It impacts the recruiters and talks about your patience and diligent attitude. Organizations prefer candidates with masters in engineering, computer science, and other relevant disciplines with formal training in Data Engineering. The mean salary of Data engineers with a master's degree is $1,06,629.
How to Boost Your Data Engineer Salary?
You may get a job with the salary you desire. However, there are instances when you have to adjust to a lesser salary. Here are a few helpful tips to bring your salary to the desired level or more.
1. Expand Your Skill Set
The simplest and straightforward way is to widen your skill sets. Practice more with SQL and Python to get fluent in those languages. Follow the latest market trends to understand what the market demands, and accordingly upgrade yourself. A training course in Online Data Science Certification helps you to expand your skill sets.
E.g., the requirement for Data engineers to have sound knowledge of cloud engineering and architecture is increasing. Getting experienced with these skills and relevant techniques will add more value to your position.
Payscale.com suggests upskilling with MapReduce results in a salary rise of around 27%. Other skills include Apache Airflow, which amounts to a hike of 16%, Apache Kafka to 15%, and JavaScript leads to an increase of 23%. Indeed.com suggests Redis as the most recommended skill, helping to hike the salary by 15.34% and CAP increasing it by 41.93%.
2. Choose the Right Location
Location plays an important role in offering a salary. Commonly factors like living cost and the job demand in a particular city play a major role in benchmarking the salary. An employee in New York City or San Francisco comparatively earns more than in other cities.
3. Gain More Experience
There's no great teacher than experience. Wherever you work, you may not get the overall exposure to become a seasoned data engineer. The best way to gain experience is to participate in open-source projects whenever you find free time. Documenting your work on Stack Overflow or GitHub will help you get better exposure. A few team leaders look for new talent on these forums.
4. Pursue a New Degree or Certification
Upgrading yourself with a new degree is a standard norm today. The more qualifications or certifications on your resume more is the scope to earn a job. In addition, it marks a positive impact on your recruiters about you dedicating your free time to building your future. They also find you trustworthy of being beneficial to their organization. You can opt for upGrad's Data Science Online Courses to upskill yourself.
Herewith are a few courses you can pursue to make yourself demanding.
- AWS Certified Big Data Specialty: AWS Certification demonstrates to potential employers that you possess the technical knowledge and experience necessary to carry out complicated data analytics.
- Azure Data Engineer Associate: The Microsoft Azure Data Engineer Certificate will provide you with a significant advantage in terms of employment and income.
- Cloudera Data Platform (CDP): You will discover how to track and secure data across all contexts while doing quick and simple analyses on it.
- Google Cloud Professional Data Engineer: This course is intended for more seasoned data analysts who are curious to deepen their understanding of the principles of big data and machine learning into a more advanced understanding of practical data engineering.
- IBM Certified Solution Architect - Data Warehouse V1: A person who can design, plan, and architect a data warehouse system is known as an IBM Certified Solution Architect - Data Warehouse V1.
- SAS Certified Big Data Professional certification: The need for SAS capabilities among organizations nowadays is very high. Learning those abilities and confirming them can open up new opportunities.
Top Paying Industries for Data Engineers in the US
Since 2021, the crown of the busiest and most demanding profile has been taken over by Data Engineers from Data Scientists. (Source: Data Science Interview Report by interviewquery.com) Herewith is a list of top-paying industries for Data Engineers in the USA.
- Technology
- Finance
- Healthcare
- Scientific Research
- Infrastructure
- Aerospace
What are the Data Engineer Salaries in Top Companies in the US?
Herewith is a list of a few top-paying companies for Data Engineers as per indeed.com, listing the average salary of data engineers in USA.
Company Name | Salary per year |
---|---|
Grainger | $1,76,992 |
Meta | $1,75,734 |
Netflix | $2,64,391 |
Glassdoor.com displays the following data.
Company Name | Salary per year |
---|---|
Meta | $1,75,830 |
Cisco Systems | $1,79,005 |
Amazon | $1,40,378 |
Capital One | $1,28,965 |
Note: The compensation depends on certain factors like qualification, experience, skill levels, etc.
Top Paying Cities for Data Engineers in the US
The following is a list of cities listed with average salaries for data engineers.
City | Salary per year |
---|---|
San Jose | $1,75,868 |
Los Angelos | $1,60,389 |
San Fransisco | $1,35,569 |
Chicago | $1,28,965 |
New York | $1,35,122 |
Boston | $1,19,089 |
Austin | $1,18,294 |
Atlanta | $1,16,085 |
Dallas | $1,12,217 |
Conclusion
Today, the demand for data engineers is ever-increasing. All companies have data scientists who are looking for data engineers to work on the data gathered by data analysts. Data engineering offers a lucrative career in the upcoming years in every industry segment and top-notch companies. Anyone can become a Data Engineer irrespective of a degree. Though a bachelor's or master's degree is essential to grab a job in some companies, an excellent mastery of programming skills can outdo this pre-condition. Hope this blog gives you a clear understanding of data engineer salary in USA.
Frequently Asked Questions (FAQs)
1. Is a data engineer internship a good way to get a job in the US?
There's a high demand for data engineering interns. As per NACE Center for Career Development and Talent Acquisition, a paid internship paves the way to getting a job. Moreover, graduates who work as interns have a high probability of earning a job than those who don't intern.
2. What is considered to be a good data engineer salary in the US?
According to Glassdoor.com, the average salary of a data engineer is $1,14,520. Indeed.com gives an amount of $134,138. You can consider your salary good if it exceeds the mean level.
3. Who gets paid more, data engineers or data scientists in the US?
Averagely, a data engineer earns up to $90,830, while a data scientist earns $91,470. It doesn't show much difference when observed from the surface level. But on the bottom line, a data scientist earns more than a data engineer by almost 20 to 30%.
4. Do data engineers make more than ML engineers in the US?
ML engineers earn more than data scientists. Data scientists earn more than data engineers. So indirectly, ML engineers earn more than data engineers. But the catch is openings for data engineers are more than for ML engineers.
5. Is data engineering a high-paying job in America?
Data engineers can get a hefty salary if they can earn a job in top-performing companies. If employed with a mid-sized company, a data engineer can upgrade and upskills with relevant certifications and techniques and try to get into a bigger company.