With its wide variety of applications, high pay, and availability of job opportunities, there are many reasons why people are attracted to data engineering. While it’s unclear how the advance of generative AI models will impact the field, interest in data engineering doesn’t appear to be waning.
“There has been, for quite a while, a lot of opportunities in data engineering,” says Cantay Caliskan, an associate professor at the University of Rochester’s Goergen Institute for Data Science. “The trend has been (upward), growth every year—better than the overall economy.”
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For those who are interested in pursuing data engineering jobs, here are 10 of the field’s highest-paying roles. Many of these titles share overlapping responsibilities.
10. Business intelligence developer
Top-paying companies: Amazon, Google, Microsoft
Salary: $102,293, according to Indeed.
Top-paying localities: New York, N.Y. ($117,013), Dallas, Texas ($112,108), Chicago, Ill. ($98,037), according to Indeed.
Through the use of various tools, business intelligence developers are able to extract insights from complex data. These insights allow organizations to predict trends, improve processes, make better decisions, and inform business strategies.
“Those are individuals who are more in a business setting and work more on applications than on theories,” explains Linda Ng Boyle, vice dean of research at the New York University Tandon School of Engineering.
9. Information systems engineer
Top-paying companies: Cisco, Intel, Apple
Salary: $111,467, according to Indeed.
Top-paying localities: Herndon, Va. ($166,728), Annapolis Junction, Md. ($158,905), Chantilly, Va. ($149,420), according to Indeed.
Information systems engineers create networks and databases to process information in support of business operations. This role requires a high level of technical skill and an understanding of programming languages in order to test systems and write code. These engineers ensure the security and stability of networks and endeavor to prevent outside parties from unauthorized access to data.
“Information systems engineers have to understand the top-down view and try to understand how it relates together,” Boyle says. “It’s very much like a data engineer. They have to understand all of the information that’s coming in and understand how it works together.”
8. Data scientist
Top-paying companies: Microsoft, Google, Facebook
Salary: $123,073, according to Indeed.
Top-paying localities: Bellevue, Wash. ($171,112), Palo Alto, Calif. ($169,487), Seattle, Wash. ($141,459), according to Indeed.
The role of research data scientist is interconnected to that of data engineer, though both have their own responsibilities and objectives. Where a data engineer develops, builds, tests, and maintains architectures like databases, a data scientist cleans and organizes data, then performs descriptive statistics to provide insights and builds models to meet a business’ needs.
7. Data science manager
Top-paying companies: Meta, Apple, Airbnb
Salary: $126,506, according to Indeed.
Top-paying localities: Menlo Park, Calif. ($218,750), San Francisco, Calif. ($215,761), Seattle, Wash. ($185,958), according to Indeed.
Data science managers are leaders who are crucial in boosting business performance through strategically executing data science initiatives. This role manages data science projects from conception to implementation. Data science managers help optimize data-driven strategies, improve efficiencies, align the data science team’s efforts with a business’ objectives, and allow for better decision making.
6. Data/AI engineer
Top-paying companies: OpenAI, Anthropic, ByteDance/TikTok
Salary: $126,676, according to Indeed.
Top-paying localities: San Jose, Calif. ($169,927), San Francisco, Calif. ($159,119), McLean, Va. ($140,687), according to Indeed.
Data engineers build and sustain data infrastructures to ensure that there is an efficient flow of data across applications and servers. The systems they create store, manage, and process substantial volumes of data. Because of their work, data scientists and analysts are able to use this data for comprehensive analytics.
“A data engineer or data science engineer is someone who knows how to do manipulations with the data and provide insights,” says Boyle. “They do testing to validate that the system architecture is correct, that we have the infrastructure to house all that data so that we can share it in the data repository.”
Artificial intelligence (AI) engineers create, program, and train algorithms that comprise AI in order to make it function like a human brain. This role requires understanding of data engineering, data science, programming, and software development.
5. Cloud data engineer
Top-paying companies: Google, Ford Motor, Deloitte
Salary: $127,113, according to Indeed.
Top-paying localities: Fort Worth, Texas ($153,074), Washington. D.C. ($142,435), New York, N.Y. ($134,563), according to Indeed.
With a specialization in creating and managing data storage solutions and workflow with cloud environments, cloud data engineers crucially ensure that an organization can access and process their data securely. This role allows organizations to optimize their data pipelines, make data-driven decisions, scale data infrastructure, and ensure that data is sharable.
4. Database architect
Top-paying companies: IBM, Amazon, Bank of America
Salary: $129,951, according to Indeed.
Top-paying localities: Austin, Texas ($159,198), Sacramento, Calif. ($152,062), Dallas, Texas ($136,577), according to Indeed.
Description: Database architects specialize in creating large-scale databases in order to organize and store large amounts of data. The work they do helps organizations understand their data needs and facilitates secure, efficient databases. Database architects are experts in information management, data modeling, and database technologies.
3. Enterprise data architect
Top-paying companies: IBM, Amazon, Booz Allen Hamilton
Salary: $141,681, according to Indeed.
Top-paying localities: Pleasanton, Calif. ($175,975), New York, N.Y. ($167,452), Washington, D.C. ($136,128), according to Indeed.
An enterprise data architect provides a wide overview of an organization’s processes and assets. They can expand and optimize data and data pipeline architectures for an entire enterprise, implement data pipelines, and ensure that data sets can be easily consumed by viewers, among other responsibilities. Enterprise data architects frequently collaborate with business-facing users, architects, analysts, developers, and data scientists to ensure that an organization’s strategies and architectures remain consistent.
2. Lead data scientist/senior data scientist/senior data scientist manager
Top-paying companies: Facebook, Snap, Intuit
Salary: $160,122, according to Indeed.
Top-paying localities: Santa Clara, Calif. ($233,563), San Francisco, Calif. ($190,548), New York, N.Y. ($168,564), according to Indeed.
Lead data scientists create techniques and analytic applications to take raw data and turn it into meaningful information. Through the use of data modeling, data mining, machine learning, and other processes, lead data scientists make sense of large datasets. This role also helps validate results and helps guide companies to explore new paths.
“They act like a quality check on what data scientists do,” Caliskan says. “They know the expectations of the company better and have some experience knowing which models lead to which outcomes.”
1. Data engineering manager
Top-paying companies: Meta, Amazon, Accenture
Salary: $249,000, according to Glassdoor.
Top-paying localities: Berkeley, Calif. ($157,043), New York, N.Y. ($151,004), Renton, Wash. ($150,551), according to ZipRecruiter.
In this leadership role, data engineering managers oversee the administrative aspects and projects of an organization’s data team. These are generally people with a decade or two of experience in the field of data science who now manage data engineers as they create, install, and maintain major processing systems and other infrastructure. They may also help develop new generative AI models.
The takeaway
According to Zippia, the data engineers have a projected job growth rate of 21% between 2018 to 2028, with about 284,100 new jobs becoming available over the next decade. Even with advances in generative AI, this field is likely to continue to grow and offer well paying and intriguing jobs.“If you like to play with data, if you like to visualize data, if you like math, statistics, it’s a great job,” Boyle says.
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