NLP Engineer vs Database Administrator: Which Pays More?
Side-by-side salary comparison by city, experience level, and career growth outlook. Data reflects current market rates.
NLP Engineer
Build natural language processing systems and text AI models.
Database Administrator
Design, implement, and maintain databases for performance, security, and reliability.
NLP Engineer earns more on average — the national median is $23,552/year (24%) higher than a Database Administrator. However, salaries vary significantly by city, employer, and experience level — see the city-by-city breakdown below.
NLP Engineer vs Database Administrator — Salary by City
National median figures in USD across top cities.
| City | NLP Engineer | Database Administrator | Difference |
|---|---|---|---|
| San Francisco, CA | $175,055 | $143,960 | NLP +$31,095 |
| New York, NY | $135,980 | $113,900 | NLP +$22,080 |
| Seattle, WA | $174,364 | $137,758 | NLP +$36,606 |
| Austin, TX | $137,212 | $110,792 | NLP +$26,420 |
| Chicago, IL | $129,954 | $100,682 | NLP +$29,272 |
| Boston, MA | $156,119 | $127,909 | NLP +$28,210 |
| London, UK | £94,915 | £77,179 | NLP +$17,736 |
| Toronto, Canada | CA$156,823 | CA$127,247 | NLP +$29,576 |
Frequently Asked Questions
Does a NLP Engineer or Database Administrator earn more?+
A NLP Engineer earns more on average. The national median salary for a NLP Engineer is $120,230/year, compared to $96,678/year for a Database Administrator — a difference of $23,552 (24%).
Which has better career growth — NLP Engineer or Database Administrator?+
NLP Engineer roles are growing at 42% YoY while Database Administrator demand is growing at 8% YoY. NLP Engineer has stronger near-term demand growth.
Can you switch from NLP Engineer to Database Administrator?+
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 — NLP Engineer or Database Administrator?+
NLP Engineer has a lower AI automation risk (20% vs 42%). Based on Oxford Martin School and McKinsey 2023 analysis.