Side-by-side distribution
Data Engineer
$170,000
median · per year, annualized USD
- Disclosing
- 33.1%
- Live roles
- 3,338
MLOps
$190,000
median · per year, annualized USD
- Disclosing
- 20.3%
- Live roles
- 133
Highest-paying jobs
Senior Data Engineer
Senior Data Engineer
Data Engineer
Senior Data Engineer
Forward Deployed Engineer, Data Engineering
Staff / Principal Data Engineer
Senior Data Engineer
Senior Data Engineer
Data Engineer
Senior Data Engineer
Highest-paying jobs
Senior Machine Learning Engineer, DevOps/SRE
Staff Machine Learning Operations Engineer
Staff Machine Learning/MLOps Engineer
Senior Data Engineer, MLOps [Remote-US]
Senior, ML Engineer - ML Ops Framework
Senior, ML Engineer - ML Ops Framework
Senior Machine Learning Operations Engineer
Staff ML/LLM Ops Engineer
Artificial Intelligence Machine Learning Engineer 3 - NLP/MLOPS
Machine Learning Operations Engineer
Top companies hiring
| Company | Median | Roles |
|---|---|---|
Speechify
|
$170,000 | 102 |
Mindrift
|
$76,960 | 59 |
Accenture Federal Services
|
$153,850 | 22 |
Esri
|
$134,264 | 16 |
Olsson
|
$125,000 | 15 |
|
Anduril Industries
|
$170,000 | 14 |
OpenAI
|
$308,250 | 12 |
Snowflake
|
$231,141 | 12 |
Top companies hiring
| Company | Median | Roles |
|---|---|---|
|
Garner Health
|
$297,500 | 2 |
|
Torc Robotics
|
$249,000 | 2 |
|
Quanata
|
$256,500 | 1 |
|
Roku
|
$254,875 | 1 |
|
LVT
|
$242,650 | 1 |
Instacart
|
$212,750 | 1 |
|
Captivation Software
|
$200,000 | 1 |
Cimgroup
|
$200,000 | 1 |
Data Engineer salary by location
| Location | Median | Roles |
|---|---|---|
| San Francisco | $216,000 | 165 |
| New York | $200,250 | 162 |
| Seattle | $191,100 | 50 |
| Austin | $185,000 | 25 |
| Boston | $172,250 | 28 |
| Atlanta | $170,000 | 11 |
| Chicago | $168,000 | 32 |
| Los Angeles | $160,000 | 20 |
| Toronto | $150,000 | 33 |
| Denver | $145,150 | 25 |
Data Engineer vs MLOps: which pays more?
The median for Data Engineer is $170,000 per year (typically $139,848–$207,500), versus $190,000 for MLOps ($172,500–$233,188). That puts MLOps about 12% ahead at the median.
Both figures are computed live from active listings on JobsRadar and normalized to annualized USD, so Data Engineer and MLOps are compared on equal terms regardless of the currency each role was originally posted in. Only roles that publish a salary range feed the medians; numbers refresh every few hours as new roles post and older ones close, so this comparison reflects the market right now rather than a fixed survey. Use it as a directional benchmark when weighing one path against the other.