Data Engineering Salary: Your 2023 Guide

Written by Coursera • Updated on

Discover how much a professional in data engineering earns in different companies, cities, and with different levels of experience and explore whether this is the career for you.

[Featured Image]:  A male data engineer is wearing a blue shirt and dark jacket.  He is working  at his laptop, at his desk in an office with other team members.

As a data engineer, your role is to organize databases and data warehouses, and optimize them for data storage and retrieval. Data engineers help companies make sense of big data with SQL, NoSQL, or hybrid infrastructures. 

It's easier than ever to collect, store, and analyze massive amounts of data. That has consequently increased the demand for database engineer skills and experience. According to Glassdoor, data engineers often earn an annual salary of over $110,000 a year [1].

In this guide, you’ll learn what data engineers do, what can affect data engineer salaries, and how you can get started on this exciting career path. 

What does a data engineer do?

Data engineers are responsible for the engineering behind the systems that store, extract, and process data. They build and maintain applications' databases and manage the infrastructure that allows them to run. As a data engineer, you might be responsible for a SQL data store and a MongoDB NoSQL data warehouse, where you’ll take care of all the activities that have to do with ensuring that data is accessible.

Data engineers are also part of a team that includes software engineers and developers, data analysts, and designers. Together, these professionals have the expertise to collect and manipulate data others use to achieve critical business objectives.

Data engineer responsibilities vary widely by organization. As a data engineer, you may do some or all of the following:

  • Design indexes on data stores (where queries will be fast) 

  • Choose the best storage technology (SQL or NoSQL

  • Ensure that the datastore is up-to-date and replicating it across multiple machines 

  • Tune data warehouses 

  • Create query plans and validate results

  • Identify patterns in historical data 

  • Analyze and optimize database performance

In a career as a data engineer, you’ll combine cutting-edge technical skills with creativity and often do so in business-critical applications.

How much do data engineers make?

According to Glassdoor, the total annual pay a data engineer earns is $111,998, including base salary and additional pay like bonuses and profit sharing [1]. The average total pay for a senior data engineer, meanwhile, is $154,989 a year. Generally, you can expect to earn a salary that is higher than average as a data engineer.

Note: Total pay is the combined amount of Glassdoor users’ reported average salary and additional pay, which could include profit sharing, commissions, cash bonuses, or tips.

Factors affecting salary

How much you’ll earn as a data engineer depends on your level of education, certifications, years of experience, company size, industry, and location. Here's what you need to know:


Bachelor's degrees are often the minimum requirement for data engineering positions. Companies often require a master's degree or professional doctorate and are typically looking to hire senior-level data engineers with proven leadership skills and industry experience. Advanced degrees can increase your earning potential by elevating you more rapidly to senior roles. 


Specialized certifications, such as Cloudera Certified Data Engineer, demonstrate specific skills employers seek. Certifications from IBM, Amazon, Google, Oracle, and Microsoft can also help you earn more and get jobs in specialist roles. Here are some data engineer certifications to consider:

  • Google Certified Data Engineer Certification

  • Data Engineer Certifications by Microsoft

  • SAS Certified Big Data Professional

  • Google Professional Data Engineer

  • Data Science Council of America (DASCA) Associate Big Data Engineer

  • Data Science Council of America (DASCA) Senior Big Data Engineer

  • Amazon Web Services (AWS) Certified Data Analytics – Specialty

  • Cloudera Data Platform Generalist Certification

Level of experience 

As you gain more experience as a data engineer, your salary will likely increase. According to data from Payscale, data engineers with one to four years of experience make an average annual salary of $89,715 [2]. The average yearly salary for professionals with five to nine years of experience increases to $108,537. 

The average annual salary for professionals with 10-19 years of experience increases to $117,582. The average yearly salary for professionals with over 20 years of experience is $117,582. With experience, you can usually expect to move into more senior roles.


There are around 6500 data engineers in the country. How much you'll earn differs by location. At least a part of the reason for salary disparity between regions is that it costs less to live in some areas based on a metric that measures the difference in cost of living in the US, called the real personal consumption expenditure (PCE). Here's the average annual pay engineers earn in several cities around the US, according to Glassdoor:

  • Austin, TX: $116,204 [18]

  • Boston, MA: $111,905 [7]

  • Charlotte, NC: $110,158 [22]

  • Chicago, IL: $128,522 [4]

  • Columbus, OH: $123,355 [11]

  • Dallas, TX: $114,671 [20]

  • Denver, CO: $110,726 [16]

  • Detroit, MI: $123,891 [19]

  • El Paso, TX: $114,553 [23]

  • Houston, TX: $109,383 [8]

  • Indianapolis, IN: $102,391 [15]

  • Los Angeles, CA: $113,553 [5]

  • Las Vegas, NV: $117,015 [24]

  • Nashville, TN: $118,432 [21]

  • New York, NY: $116,291 [3]

  • Philadelphia, PA: $129,828 [6]

  • Phoenix, AZ: $112,311 [13]

  • San Antonio, TX: $115,933 [10]

  • San Diego, CA: $105,119 [9]

  • San Francisco, CA: $129,160 [12]

  • San Jose, CA: $118,095 [14]

  • Seattle, WA: $132,324 [17]

  • Salt Lake City, UT: $108,463 [25]

Company size

Company size often impacts data engineer salaries. Companies offering higher salaries tend to be more significant employers—such as IBM, Amazon, Meta,  and Google—and often have larger, more experienced data science teams.

Job title variations and salary

Data engineer job titles vary by company, tasks, and skills required. Here are some common titles that data engineers can have:

  • Cloud data engineer: $116,497 [32]

  • AI engineer: $126,774 [26]

  • Big data engineer: $116,675 [33]

  • Data science engineer: $127,966 [29]

  • Database architect: $143,601 [31]

  • Enterprise data architect: $172,872 [28]

  • Hadoop engineer: $143,322 [34]

  • Information systems engineer: $92,340 [27]

How to become a data engineer: Next steps

To become a data engineer, you should work to build and demonstrate a solid competency base across database technologies and coding. Typically, data engineers need at least a bachelor’s degree, some certifications, and professional experience.

Getting started with data engineering

If you’re ready to take the next step in your data engineering career, you may want to consider the Data Engineering Foundations Specialization, offered by IBM, or the IBM Data Engineering Professional Certificate. These provide you with the opportunity to learn foundational knowledge in data engineering.



Data Engineering Foundations

Build the Foundation for a Data Engineering Career. Develop hands-on experience with Python, SQL, and Relational Databases and master the fundamentals of the Data Engineering ecosystem.


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Information Engineering, Python Programming, Extraction, Transformation And Loading (ETL), Relational Database Management System (RDBMS), SQL, Data Science, Database (DBMS), NoSQL, Data Analysis, Pandas, Numpy, Jupyter notebooks, Web Scraping, Extract Transform Load (ETL), Database (DB) Design, Database Architecture, Postgresql, MySQL, Cloud Databases

Article sources


Glassdoor, “How much does a Data Engineer make?,13.htm.” Accessed December 21, 2022.

Written by Coursera • Updated on

This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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