Johnson & Johnson is seeking a Staff Field Reliability Engineer for their Robotics and Digital R&D team in Santa Clara, CA. The role involves leading reliability engineering efforts, analyzing field data, and collaborating with cross-functional teams to enhance product reliability for advanced robotic systems in healthcare
Job Summary
As a leader in our team, you will join us in our journey to deliver some of the most advanced medical robotic systems in the world.
This role will define field reliability metrics, establish the infrastructure for monitoring product performance in the field, and partner closely with Design for Reliability, Failure Analysis, Design Engineering, Service Engineering, and field organizations to reduce customer-impacting issues and verify the effectiveness of corrective actions.
The anticipated base pay range for this position is $134,000.00 to $231,150.00.
Matching Summary
Match Score: 85
Johnson & Johnson is seeking a Staff Field Reliability Engineer for their Robotics and Digital R&D team in Santa Clara, CA. The role involves leading reliability engineering efforts, analyzing field data, and collaborating with cross-functional teams to enhance product reliability for advanced robotic systems in healthcare.
Salary
Base: $134,000.00 - $231,150.00; Bonus/Equity: Eligible for annual performance bonus; Benefits: Medical, dental, vision, life insurance, disability, retirement plan, savings plan, long-term incentive program
Skills & Requirements
Must-have
field return data analysis
failure analysis investigations
reliability metrics and dashboards
preventive maintenance methods
root-cause investigation methodology
Nice-to-have
design for reliability
iterative product development
inclusive work environment
diversity of thought
Key Requirements
Bachelor’s degree in Electrical, Mechanical, Materials Engineering or related technical field
8+ years experience in reliability engineering, field engineering, failure analysis, or equivalent role
Proficiency with statistical reliability methods
Experience with common analysis tools (Excel/Power BI/Tableau, Python, R, Minitab, or JMP)