Backend Developer vs Analytics Engineer: Which Pays More?
Side-by-side salary comparison by city, experience level, and career growth outlook. Data reflects current market rates.
Backend Developer
Build server-side APIs, databases, and business logic.
Analytics Engineer
Build and maintain the data models and pipelines that power business intelligence.
Backend Developer earns more on average — the national median is $15,895/year (13%) higher than a Analytics Engineer. However, salaries vary significantly by city, employer, and experience level — see the city-by-city breakdown below.
Backend Developer vs Analytics Engineer — Salary by City
National median figures in USD across top cities.
| City | Backend Developer | Analytics Engineer | Difference |
|---|---|---|---|
| San Francisco, CA | $194,530 | $171,525 | Backend +$23,005 |
| New York, NY | $167,456 | $147,203 | Backend +$20,253 |
| Seattle, WA | $193,111 | $173,765 | Backend +$19,346 |
| Austin, TX | $151,541 | $131,230 | Backend +$20,311 |
| Chicago, IL | $146,538 | $125,515 | Backend +$21,023 |
| Boston, MA | $173,670 | $158,382 | Backend +$15,288 |
| London, UK | £73,942 | £93,991 | Backend $20,049 |
| Toronto, Canada | CA$126,152 | CA$163,067 | Backend $36,915 |
Frequently Asked Questions
Does a Backend Developer or Analytics Engineer earn more?+
A Backend Developer earns more on average. The national median salary for a Backend Developer is $135,980/year, compared to $120,085/year for a Analytics Engineer — a difference of $15,895 (13%).
Which has better career growth — Backend Developer or Analytics Engineer?+
Backend Developer roles are growing at 22% YoY while Analytics Engineer demand is growing at 38% YoY. Analytics Engineer has stronger near-term demand growth.
Can you switch from Backend Developer to Analytics Engineer?+
Yes. Many professionals transition between these roles, especially since both are in the same category. Shared skills include: Python.
Which is harder to automate — Backend Developer or Analytics Engineer?+
Analytics Engineer has a lower AI automation risk (35% vs 45%). Based on Oxford Martin School and McKinsey 2023 analysis.