Reliability Engineer: Lead Predictive Maintenance & RCA

the-pivot-group-careers

Hudsonville (MI)

On-site

USD 81,000 - 121,000

Full time

6 days ago

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Job summary

The Pivot Group Network in Hudsonville, MI is seeking a Reliability Engineer to design and implement maintenance programs that improve equipment uptime and reliability.

You will analyze failures, lead root-cause investigations, and collaborate with operations and maintenance teams to optimize preventive and predictive maintenance strategies.

Candidates should have a mechanical or industrial engineering background and hands-on experience with CMMS/EAM systems and data analysis.

Qualifications

Bachelors degree in Engineering (Mechanical, Electrical, Industrial, or similar).
3+ years in manufacturing reliability engineering or maintenance.
Proficient in RCA and problem-solving methodologies.
Strong understanding of predictive and preventive maintenance techniques (vibration analysis, thermography, oil analysis).
Experience with CMMS and Enterprise Asset Management (EAM) software.
Knowledge of statistical analysis for reliability data and failure prediction.

Responsibilities

Develop and implement predictive maintenance strategies.
Analyze equipment failures and provide root cause analysis.
Optimize preventive maintenance programs and schedules.
Identify and execute reliability improvement projects.
Collaborate with cross-functional teams on new equipment design and installation.
Track and report on key reliability metrics and performance indicators.

Skills

RCA

Vibration analysis

Thermography

Oil analysis

Data analysis

CMMS

Education

Bachelor's degree in Engineering

Tools

CMMS

EAM

Job description

The Pivot Group Network in Hudsonville, MI is seeking a Reliability Engineer to design and implement maintenance programs that improve equipment uptime and reliability.

You will analyze failures, lead root-cause investigations, and collaborate with operations and maintenance teams to optimize preventive and predictive maintenance strategies.

Candidates should have a mechanical or industrial engineering background and hands-on experience with CMMS/EAM systems and data analysis.

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