Data Engineer vs Enterprise Architect: 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.
Enterprise Architect
Align IT architecture with business strategy at the enterprise level.
Data Engineer earns more on average — the national median is $22,920/year (20%) higher than a Enterprise Architect. However, salaries vary significantly by city, employer, and experience level — see the city-by-city breakdown below.
Data Engineer vs Enterprise Architect — Salary by City
National median figures in USD across top cities.
| City | Data Engineer | Enterprise Architect | Difference |
|---|---|---|---|
| San Francisco, CA | $202,499 | $174,584 | Data +$27,915 |
| New York, NY | $131,540 | $138,849 | Data $7,309 |
| Seattle, WA | $105,430 | $170,016 | Data $64,586 |
| Austin, TX | $153,836 | $128,905 | Data +$24,931 |
| Chicago, IL | $154,010 | $126,306 | Data +$27,704 |
| Boston, MA | $179,962 | $150,648 | Data +$29,314 |
| London, UK | £108,711 | £92,059 | Data +$16,652 |
| Toronto, Canada | CA$181,115 | CA$158,112 | Data +$23,003 |
Frequently Asked Questions
Does a Data Engineer or Enterprise Architect earn more?+
A Data Engineer earns more on average. The national median salary for a Data Engineer is $139,500/year, compared to $116,580/year for a Enterprise Architect — a difference of $22,920 (20%).
Which has better career growth — Data Engineer or Enterprise Architect?+
Data Engineer roles are growing at 34% YoY while Enterprise Architect demand is growing at 18% YoY. Data Engineer has stronger near-term demand growth.
Can you switch from Data Engineer to Enterprise Architect?+
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 Enterprise Architect?+
Enterprise Architect has a lower AI automation risk (25% vs 42%). Based on Oxford Martin School and McKinsey 2023 analysis.