Platform Engineer vs Data Analyst: Which Pays More?
Side-by-side salary comparison by city, experience level, and career growth outlook. Data reflects current market rates.
Platform Engineer
Build and maintain internal developer platforms and tooling.
Data Analyst
Transform raw data into actionable business insights through analysis and reporting.
Platform Engineer earns more on average — the national median is $10,190/year (11%) higher than a Data Analyst. However, salaries vary significantly by city, employer, and experience level — see the city-by-city breakdown below.
Platform Engineer vs Data Analyst — Salary by City
National median figures in USD across top cities.
| City | Platform Engineer | Data Analyst | Difference |
|---|---|---|---|
| San Francisco, CA | $147,719 | $129,659 | Platform +$18,060 |
| New York, NY | $119,390 | $108,724 | Platform +$10,666 |
| Seattle, WA | $138,263 | $102,930 | Platform +$35,333 |
| Austin, TX | $112,024 | $101,065 | Platform +$10,959 |
| Chicago, IL | $106,120 | $92,625 | Platform +$13,495 |
| Boston, MA | $127,664 | $113,607 | Platform +$14,057 |
| London, UK | £79,847 | £71,596 | Platform +$8,251 |
| Toronto, Canada | CA$131,262 | CA$116,846 | Platform +$14,416 |
Frequently Asked Questions
Does a Platform Engineer or Data Analyst earn more?+
A Platform Engineer earns more on average. The national median salary for a Platform Engineer is $99,130/year, compared to $88,940/year for a Data Analyst — a difference of $10,190 (11%).
Which has better career growth — Platform Engineer or Data Analyst?+
Platform Engineer roles are growing at 26% YoY while Data Analyst demand is growing at 28% YoY. Data Analyst has stronger near-term demand growth.
Can you switch from Platform Engineer to Data Analyst?+
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 — Platform Engineer or Data Analyst?+
Platform Engineer has a lower AI automation risk (36% vs 50%). Based on Oxford Martin School and McKinsey 2023 analysis.