Reliability Engineer - Predictive Maintenance Leader

Marsveterinary; Sparks, Northern (NV, KY); Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Best-in-class learning and development

Mars University access

Company bonus

Job summary

Mars seeks a Reliability Engineer to eliminate maintenance losses by developing proactive maintenance strategies for site equipment. You will lead PM optimization, RCM, RCA, and other reliability tools, coaching technicians to use advanced maintenance practices.

The role focuses on achieving reliability through data-driven analyses, preventative and predictive maintenance, and strong cross-functional collaboration with planners, supervisors, and site leadership.

Qualifications

• Bachelor’s degree in a technical discipline or 10+ years in manufacturing.
• Experience developing maintenance strategies to reduce losses.
• Ability to analyze data to identify root causes.
• Experience with high-speed packaging equipment.
• Leadership, organizational and time management skills.
• Proven ability to manage multiple projects within budget.

Responsibilities

• Define and refine maintenance strategies for new and existing equipment.
• Lead reliability improvement programs and tool usage.
• Coordinate with planners to schedule PM/PdM services.
• Analyze failure data to set PF curves and prioritization.
• Provide technical advice to maintenance owners.
• Lead training and coaching of technical staff.
• Ensure spare parts lists and manuals are maintained.

Skills

Leadership

Project management

Communication

Data analysis

Problem solving

Team coaching

Education

Bachelor’s degree in technical discipline

10 years of related experience in manufacturing

Tools

SAP PM

Excel

Job description

Mars seeks a Reliability Engineer to eliminate maintenance losses by developing proactive maintenance strategies for site equipment. You will lead PM optimization, RCM, RCA, and other reliability tools, coaching technicians to use advanced maintenance practices.

The role focuses on achieving reliability through data-driven analyses, preventative and predictive maintenance, and strong cross-functional collaboration with planners, supervisors, and site leadership.