Equipment Specialist

Job Title:

Engagement Type:

Location:

Experience Required:

Primary Skill :

Job Title:

Experience Required:

Secondary Skills:

Project Overview :

Reliability Driven Execution (RDE)

Key Responsibilities :

• Act as the

  onsite execution lead

  for the pilot implementation of rotating equipment asset strategies.
• Validate, reconcile, and secure approvals for asset strategies configured in

  GE APM

  .
• Coordinate with

  Operations and Maintenance teams

  to ensure accurate execution in

  SAP PM and eSOMS

  .
• Perform

  field inspections and verification

  of rotating equipment to support strategy validation.
• Collaborate with cross-functional stakeholders to ensure

  standardization and scalability

  of the pilot model.
• Utilize

  GE APM (Meridium)

  for reliability analysis and strategy execution.
• Lead

  client discussions and technical workshops

  .
• Ensure high client satisfaction through proactive communication and issue resolution.
• Work closely with

  offshore teams across multiple time zones

  .
• Coordinate reporting, analysis, and execution tracking between onsite and offshore teams.

Required Skills & Experience :

• Bachelor’s degree in

  Mechanical Engineering

  or a related discipline.
• Strong Oil & Gas domain experience with rotating equipment such as:
• Pumps
• Compressors
• Turbines
• Motors
• Hands-on experience with:

• GE APM (Meridium)

• SAP PM

• eSOMS

• Solid understanding of:
• Asset strategy development
• Reliability-centered maintenance
• Asset lifecycle management
• Proven ability to lead onsite execution and collaborate with multidisciplinary teams.
• Excellent communication, stakeholder management, and documentation skills.

Preferred Qualifications

• Certifications such as

  CMRP, PE

  , or equivalent.
• Prior experience executing

  pilot programs

  or strategy deployments using GE APM and SAP PM.
• Familiarity with

  RDE programs

  and enterprise asset management systems.
• Exposure to

  digital reliability platforms

  and data-driven maintenance models.