Global Data Operations Engineer Salary: USD 85,000
💰 The median salary for a Data Operations Engineer is USD 85,000 per year globally
📋 This salary info is based on 8 individual annual salaries reported during 2021 - 2022
Filter by job title3D Computer Vision Researcher AI Scientist Analytics Engineer Applied Data Scientist Applied Machine Learning Scientist Applied Scientist BI Analyst BI Data Analyst Big Data Engineer Business Data Analyst Computer Vision Engineer Data Analyst Data Analytics Engineer Data Analytics Manager Data Architect Data Engineer Data Engineering Manager Data Manager Data Operations Engineer Data Science Consultant Data Science Manager Data Scientist Data Specialist Director of Data Science ETL Developer Head of Data Lead Data Engineer Lead Data Scientist Machine Learning Developer Machine Learning Engineer Machine Learning Researcher Machine Learning Scientist Machine Learning Software Engineer ML Engineer Principal Data Scientist Research Engineer Research Scientist
Filter by experience levelMid-level / Intermediate
Filter by employee residenceUnited States
Salary information details
- Job title
- Data Operations Engineer
- Experience level
- all levels
- Employee residence
- Working years
- 2021 - 2022
- Median USD
- 10th percentile USD
- 25th percentile USD
- 75th percentile USD
- 90th percentile USD
How can I contribute?
📝 Submit your salary data
Enter your own salary data for the current or past work year. It's quite simple and doesn't take more than a minute to fill out.Go to salary survey
📢 Share this site
Share our "in-less-than-a-minute survey" with others working in the field of AI/ML/Data Science. The more data we have the better for everyone.
💾 Download the data
All collected information will be updated into a public dataset regularly and provided as a download free for anyone to use.Go to download page
About this project
This site collects salary information anonymously from professionals all over the world in the AI/ML/Data Science space and makes it publicly available for anyone to use, share and play around with.
The primary goal is to have data that can provide better guidance in regards to what's being paid globally. So newbies, experienced pros, hiring managers, recruiters and also startup founders or people wanting to make a career switch can make better informed decisions.