Data Scientist and Data Engineer salaries

Ariel K
Sep 3, 2023
3 min read

Data science and data engineering are two of the hottest roles in tech. But when it comes to compensation, which of these data-centric jobs pays more? Based on national salary data, data scientists generally earn higher pay across experience levels.

Entry Level

For professionals just starting out, data scientists make a median salary of $95,000 while data engineers earn around $90,000. Data scientists come out ahead with $5,000+ higher salary for entry level roles. Their technical skills like statistics and machine learning modeling command more pay.

Mid-Career

With 3-5 years experience, data scientists again lead with median salaries reaching $115,000 annually compared to $108,000 for data engineers. The specialization and quantitative abilities data scientists gain sees their compensation outpace engineers at the mid-career stage.

Senior

For highly experienced veterans with 6+ years under their belt, data scientists make a median of $130,000 while data engineers earn $125,000. The gap closes slightly but mid-career data scientists still see a $5,000 advantage in typical salaries.

Geographic Differences

Salaries also vary significantly based on locations. In tech hubs like San Francisco and Seattle, data scientists make $140-150K versus $135K for data engineers. In other regions like the Midwest and South, data scientists earn around $115K while engineers make $105K. Data scientists consistently come out ahead.

Exceptions

In some specific industries like finance or healthcare, data engineering may be more valued and thus better compensated. Additionally, data engineers with specialties like Hadoop or cloud architecture can match or exceed data scientist salaries. But looking at overall national trends, data scientists have the pay advantage.

Key Takeaways:

- For entry level roles, data scientists typically earn $95K while data engineers make $90K

- Mid-career data scientists average $115K compared to $108K for data engineers

- Highly experienced data scientists command $130K vs $125K for data engineers

- Geography impacts pay but data scientists lead in tech hubs and other regions

- Specialized data engineers can potentially match data scientist compensation

So while both remain highly coveted and well-compensated roles, crunching the numbers shows data scientists enjoy a pay premium over data engineers at most career stages. Supply and demand economics seem to favor the technically specialized skills data scientists bring to the table. But it takes all kinds of data talent to make an impact with AI and analytics!

Sources of Data Scientist and Data Engineer salaries

Here are some of the sources we used to research typical salary ranges:

Glassdoor salary data: Provides user-submitted salaries for both data scientists and data engineers across various companies, experience levels, and geographic regions. Useful for gauging averages.
Indeed salary information: Similar to Glassdoor, aggregates user-contributed salary reports for job titles like data scientist and data engineer. Helps establish compensation ranges.
Dice Tech Salary Survey: Annual survey of thousands of tech professionals including data scientists and engineers. Gives insight into national salary trends.
BLS Occupational Outlook Handbook: Published by the US Bureau of Labor Statistics, provides median pay for related occupations like statisticians, database administrators, and software developers.
LinkedIn salary tool: Offers salary estimates based on job title, skills, location, and experience by analyzing millions of member profiles.
Hiring expert perspectives: Consulting commentary from recruiting firms and hiring managers on pay rates.
O'Reilly industry survey data: Their annual survey of data professionals includes some salary segmentation for roles.