Highest-Paid Data Science Roles & Top Salaries

Data Science roles are some of the most important jobs in any company. These roles are responsible for taking all of the data that a company collects and turning it into actionable insights.

Without these roles, companies would be unable to make sound business decisions.

Let’s take a look at the six highest-paid Data Science jobs and their corresponding salaries — fully broken down here in our Tech Salary Guide — as we explain what each role is responsible for and when the best time to hire for these positions is.

Data Science Salaries by Position, Low & High

PositionLowHigh
Data Architect$145,000$225,000
Big Data Engineer$140,000$200,000
BI Architect $125,000$190,000
Data Scientist$110,000$250,000
Data Warehouse Engineer$110,000$190,000
Data Engineer$110,000$185,000

Data Scientist Salary

Data Scientists earn an average salary range of $110,000-$250,000.

Data Scientists are responsible for taking all of the data that a company collects and turning it into business analytics for actionable insights.

They use their skills in statistics, mathematics, and computer science to clean, organize, and analyze data and usually have a background in one of these three disciplines.

When to hire a Data Scientist?

The best time to hire a Data Scientist is when a company is looking to make a major change or transition. This could be anything from a new product launch to a rebranding effort.

Data Scientists can help companies make these changes by providing insights that would otherwise be unavailable to the average person.

Data Architect Salary

Data Architects earn an average salary range of $145,000-$225,000.

A Data Architect is responsible for designing, creating, and maintaining the data infrastructure that a company uses. This includes everything from databases to data warehouses.

They work with Data Scientists to ensure that the data is properly organized and easily accessible.

When to hire a Data Architect?

The best time to hire a Data Architect is when a company is expanding its operations and improve its business operations. This could be anything from opening a new office to launching a new product.

Data Architects can help companies expand by designing and creating the data infrastructure that they need to support their growth.

Big Data Engineer Salary

Big data engineers earn an average salary range of $140,000-$200,000.

A Big Data Engineer is responsible for managing and analyzing large data sets. This includes everything from collecting data to processing it and storing it.

They use their skills in computer science and engineering to design and build the systems that a company needs to store and process its data.

When to hire a Big Data Engineer?

The best time to hire a Big Data Engineer is when a company is looking to make a serious commitment to data security, compliance, and privacy. Which, realistically should be any company that is collecting and housing any form of consumer data.

Big Data Engineers can help companies make these changes and secure their data by designing and building the systems that they need to support their growth.

BI Architect Salary

BI Architects earn an average salary range of $125,000-$190,000.

Business intelligence is a process that is used to transform data into insights that can be used to make strategic business decisions.

A BI Architect is more than a traditional business analyst. These professionals use business intelligence tools to design and implement the business intelligence infrastructure that a company uses including everything from data warehouses to reporting tools.

When to hire a BI Architect?

The best time to hire a BI Architect is when a company is looking to improve its decision-making process. This could be anything from launching a new product to expanding into new markets.

Data Warehouse Engineer Salary

Data Warehouse Engineers earn an average salary range of $110,000-$190,000.

A Data warehouse engineer designs, builds, and maintains the data warehouses that a company uses to store and process its data.

They use their skills in computer science and engineering to code and design data warehouse software that ensures all the data a company collects is stored in a safe and legally compliant manner.

When to hire a Data Warehouse Engineer?

The best time to hire a Data Warehouse Engineer is when a company is looking to improve its data management and compliance especially when it comes to cloud-based storage.

Data Engineer Salary

Data Engineers earn an average salary range of $110,000-$185,000.

A Data Engineer is different from a data warehouse engineer in that they are responsible for managing the data that is collected by a company.

This includes everything from processing it to storing it and making it accessible to those who need it.

When to hire a Data Engineer?

The best time to hire a Data Engineer is when a company is looking to improve its data management, storage, and accessibility. Data is only as good as its ability to be easily accessed, interpreted, and leveraged.


While the salary range for each job may vary depending on experience, location, and other factors, these ranges give you a good idea of what to expect when pursuing a career in data science or for building out your company’s data science team.

For a complete breakdown of all the top 13 Data Science salaries, download our 2022 Salary Guide across Tech, Creative & Digital Marketing.

Looking for your next Data Science gig? Let us help.

Every year,  Mondo helps over 2,000 candidates find jobs they love.

Need to hire Data Science Experts & Professionals?

With roles like Data Engineers and Data Scientists becoming some of the most in-demand jobs in the tech industry, it’s crucial you Data Science talent today and ensure that you’re offering competitive salaries so you don’t miss out on the high-end talent you need.

If you lack the Data Science professionals you need or want to learn more about the salary ranges for related roles, contact Mondo today.

We’ll provide you with the salary insights and candidates you need to elevate your Data Science workflow and strategies.

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