Analytics Engineer vs Data Architect: Which Pays More?
Side-by-side salary comparison by city, experience level, and career growth outlook. Data reflects current market rates.
Analytics Engineer
Build and maintain the data models and pipelines that power business intelligence.
Data Architect
Design enterprise data systems, lakes, and pipelines for scalability and governance.
Data Architect earns more on average — the national median is $30,530/year (25%) higher than a Analytics Engineer. However, salaries vary significantly by city, employer, and experience level — see the city-by-city breakdown below.
Analytics Engineer vs Data Architect — Salary by City
National median figures in USD across top cities.
| City | Analytics Engineer | Data Architect | Difference |
|---|---|---|---|
| San Francisco, CA | $171,525 | $223,662 | Analytics $52,137 |
| New York, NY | $147,203 | $176,070 | Analytics $28,867 |
| Seattle, WA | $173,765 | $213,160 | Analytics $39,395 |
| Austin, TX | $131,230 | $169,668 | Analytics $38,438 |
| Chicago, IL | $125,515 | $163,518 | Analytics $38,003 |
| Boston, MA | $158,382 | $192,776 | Analytics $34,394 |
| London, UK | £93,991 | £114,371 | Analytics $20,380 |
| Toronto, Canada | CA$163,067 | CA$200,067 | Analytics $37,000 |
Frequently Asked Questions
Does a Analytics Engineer or Data Architect earn more?+
A Data Architect earns more on average. The national median salary for a Analytics Engineer is $120,085/year, compared to $150,615/year for a Data Architect — a difference of $30,530 (25%).
Which has better career growth — Analytics Engineer or Data Architect?+
Analytics Engineer roles are growing at 38% YoY while Data Architect demand is growing at 28% YoY. Analytics Engineer has stronger near-term demand growth.
Can you switch from Analytics Engineer to Data Architect?+
Yes. Many professionals transition between these roles, especially since both are in the same category. Shared skills include: Snowflake.
Which is harder to automate — Analytics Engineer or Data Architect?+
Data Architect has a lower AI automation risk (28% vs 35%). Based on Oxford Martin School and McKinsey 2023 analysis.