Job Overview:
We are seeking a results-driven APM / APA Engineer with 6–8 years of relevant experience in asset performance improvement, predictive maintenance analytics, and digital transformation within the oil & gas or petrochemical industry. The ideal candidate will possess a Core Engineering background (preferably Mechanical or Chemical) with hands-on exposure to condition-based monitoring, reliability frameworks (RCM/FMEA/RCA), and machine learning-based predictive models.
In addition to technical responsibilities, this role will also support PMO activities, contributing to project governance, progress tracking, and alignment of project team. So, this is a hybrid role.
Key Responsibilities:
Asset Performance & Predictive Maintenance
- Develop, implement, and optimize asset strategies (PM, CBM, PdM, RBI) using Reliability-Centered Maintenance (RCM) principles.
- Lead Asset Codification, Criticality Assessment, and alignment of FMEA with CMMS failure modes.
- Deploy and fine-tune real-time equipment health monitoring using sensor data (vibration, temperature, flow, etc.).
- Build and validate ML-driven predictive maintenance models, incorporating AI pattern recognition, anomaly detection, and digital twins.
- Define and track Asset Health Indices and develop dashboards showing trends, KPIs, and predictive alerts.
- Conduct Root Cause Analysis (RCA) and link findings to predictive algorithms for improved accuracy.
- Interface with Process Historians (e.g., OSIsoft PI), CMMS (SAP, Maximo), and APM platforms (e.g., GE APM, Aspen Mtell, AVEVA Predictive Analytics).
- Participate in Risk-Based Inspection (RBI) strategy development and implementation for static equipment.
- Ensure alignment with data governance, safety, and cybersecurity standards for OT systems.
Project Management Support
- Contribute to planning, execution, and governance of predictive maintenance and asset reliability projects under the Digital Transformation Program.
- Track milestones, risks, and KPIs associated with APM/APA initiatives using PMO tools (MS Project, Power BI, Primavera).
- Collaborate with engineers, IT, operations, vendors, and data scientists to deliver high-quality outcomes.
- Maintain project artifacts including charters, WBS, test cases, and lessons learned in various projects.
- Assist in business case development for digital asset solutions and support Steering Committee presentations.
- Support adoption, training, and change management efforts.
Qualifications:
- Bachelor's degree in Mechanical, Chemical, or related engineering discipline.
- 4-6 years of experience in APM/RCM/CBM/PdM engineering within oil & gas or petrochemical sectors.
- Strong knowledge of asset failure mechanisms, maintenance optimization, and condition monitoring.
- Practical experience with predictive analytics platforms and ML/AI tools in an industrial setting.
- Familiarity with industry-standard tools such as AVEVA PI, GE APM, Aspen Mtell, SAP PM, IBM Maximo, or Honeywell Forge APM.
- Hands-on experience with process historians, DCS/SCADA data, and sensor integration.
- Working knowledge of project lifecycle, documentation standards, and governance frameworks.
- Certifications in RCM, FMEA, or Reliability Engineering are a plus.
- PMP, PRINCE2, or Agile certification is desirable but not mandatory.
- Strong communication skills with the ability to coordinate across multidisciplinary teams.
- Flexibility to travel to field sites and support hands-on diagnostic or deployment work is extremely important.
What We Offer:
- Opportunity to work on high-impact asset reliability and predictive analytics programs with leading energy clients.
- Exposure to cutting-edge technologies in the digital asset management ecosystem.
- Collaborative work environment that encourages technical innovation and cross-functional learning.
- Competitive compensation, site/project allowances, and performance-based incentives.
How to apply:
Through the following link: https://forms.gle/EDJ1TBsrXs7YqS6o8
