QA Engineer vs Data Governance Analyst: Which Pays More?
Side-by-side salary comparison by city, experience level, and career growth outlook. Data reflects current market rates.
QA Engineer
Design and execute test strategies to ensure software quality.
Data Governance Analyst
Establish and enforce policies for data quality, privacy, and compliance.
QA Engineer earns more on average — the national median is $15,360/year (17%) higher than a Data Governance Analyst. However, salaries vary significantly by city, employer, and experience level — see the city-by-city breakdown below.
QA Engineer vs Data Governance Analyst — Salary by City
National median figures in USD across top cities.
| City | QA Engineer | Data Governance Analyst | Difference |
|---|---|---|---|
| San Francisco, CA | $151,085 | $127,235 | QA +$23,850 |
| New York, NY | $126,759 | $104,917 | QA +$21,842 |
| Seattle, WA | $150,155 | $102,930 | QA +$47,225 |
| Austin, TX | $114,009 | $96,439 | QA +$17,570 |
| Chicago, IL | $115,087 | $96,264 | QA +$18,823 |
| Boston, MA | $133,460 | $114,991 | QA +$18,469 |
| London, UK | £82,816 | £67,745 | QA +$15,071 |
| Toronto, Canada | CA$136,813 | CA$119,721 | QA +$17,092 |
Frequently Asked Questions
Does a QA Engineer or Data Governance Analyst earn more?+
A QA Engineer earns more on average. The national median salary for a QA Engineer is $104,300/year, compared to $88,940/year for a Data Governance Analyst — a difference of $15,360 (17%).
Which has better career growth — QA Engineer or Data Governance Analyst?+
QA Engineer roles are growing at 12% YoY while Data Governance Analyst demand is growing at 28% YoY. Data Governance Analyst has stronger near-term demand growth.
Can you switch from QA Engineer to Data Governance 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 — QA Engineer or Data Governance Analyst?+
Data Governance Analyst has a lower AI automation risk (50% vs 62%). Based on Oxford Martin School and McKinsey 2023 analysis.