Data Engineer vs IT Support Specialist: Which Pays More?
Side-by-side salary comparison by city, experience level, and career growth outlook. Data reflects current market rates.
Data Engineer
Build and maintain data pipelines, warehouses, and ETL infrastructure.
IT Support Specialist
Provide technical support for hardware, software, and networks.
Data Engineer earns more on average — the national median is $77,640/year (126%) higher than a IT Support Specialist. However, salaries vary significantly by city, employer, and experience level — see the city-by-city breakdown below.
Data Engineer vs IT Support Specialist — Salary by City
National median figures in USD across top cities.
| City | Data Engineer | IT Support Specialist | Difference |
|---|---|---|---|
| San Francisco, CA | $202,499 | $92,808 | Data +$109,691 |
| New York, NY | $131,540 | $72,917 | Data +$58,623 |
| Seattle, WA | $105,430 | $86,967 | Data +$18,463 |
| Austin, TX | $153,836 | $69,244 | Data +$84,592 |
| Chicago, IL | $154,010 | $64,877 | Data +$89,133 |
| Boston, MA | $179,962 | $79,215 | Data +$100,747 |
| London, UK | £108,711 | £47,998 | Data +$60,713 |
| Toronto, Canada | CA$181,115 | CA$84,196 | Data +$96,919 |
Frequently Asked Questions
Does a Data Engineer or IT Support Specialist earn more?+
A Data Engineer earns more on average. The national median salary for a Data Engineer is $139,500/year, compared to $61,860/year for a IT Support Specialist — a difference of $77,640 (126%).
Which has better career growth — Data Engineer or IT Support Specialist?+
Data Engineer roles are growing at 34% YoY while IT Support Specialist demand is growing at 5% YoY. Data Engineer has stronger near-term demand growth.
Can you switch from Data Engineer to IT Support Specialist?+
Yes. Many professionals transition between these roles, especially since both are in the same category. Shared skills include: analytical thinking, communication, and industry knowledge.
Which is harder to automate — Data Engineer or IT Support Specialist?+
Data Engineer has a lower AI automation risk (42% vs 71%). Based on Oxford Martin School and McKinsey 2023 analysis.