Manager – O&G Downstream (Refinery Maintenance & Reliability – Predictive Maintenance)

Desired Experience: 8–10 years

Mandatory Skill:

• Refinery Maintenance & Reliability (Predictive Maintenance focus) with strong depth in rotary equipment and turbomachinery

Preferred Background:

• Experience with Integrated Oil Companies such as Exxon Mobil / Shell / BP

Role Purpose

Maintenance & Reliability Subject Matter Expert (SME) embedded within a digital / AI use case delivery squad, acting as the functional bridge between refinery maintenance/reliability stakeholders and cross-functional technical teams (product, data science, data engineering, architecture). The role is non-coding and focuses on shaping, translating, validating, and governing predictive maintenance and reliability analytics solutions—particularly for rotating equipment and turbomachinery—to improve equipment availability, reduce unplanned downtime, and strengthen asset integrity.

Operating Model & Reporting

• Workstream leadership role within an Agile / product-style delivery environment; responsible for end-to-end functional success of maintenance & reliability use cases from discovery to deployment.
• Interfaces with refinery maintenance, reliability, rotating equipment SMEs, and operations teams; partners closely with technical delivery teams (product managers, data scientists, data engineers, solution architects).
• Reports into Consulting Delivery Leadership and partners closely with MENA stakeholders on SC&O / Digital Ops priorities.

Key Responsibilities

• Maintenance & Reliability Use Case Discovery & Functional Leadership
  • Lead discovery workshops with maintenance/reliability and rotating equipment stakeholders to capture decision workflows, failure modes, maintenance pain points, criticality logic, operating constraints, and success criteria for predictive maintenance.
  • Own structured documentation: use case descriptions, functional requirements, assumptions, constraints, acceptance criteria, and stakeholder-ready narratives for predictive maintenance and reliability transformation.
  • Drive alignment on the transition from time-based maintenance to condition-based and predictive maintenance approaches within refinery reliability programs.
• Predictive Maintenance / Digital Twin Delivery (Non-Coding)
  • Translate maintenance and rotating equipment requirements into technical inputs (features, inputs, constraints, failure signatures, alert thresholds, and classifications) to enable deployable predictive models and digital workflows.
  • Provide domain oversight for predictive maintenance solutions that:
    • Automate preventive maintenance scheduling using condition-based parameters
    • Track planned/unplanned downtime and equipment performance metrics (including OEE where applicable)
    • Predict breakdowns using sensor/condition data and trigger actionable maintenance engineer alerts
    • Validate analytics/AI outputs and dashboards for domain realism—ensuring recommendations make operational sense for rotating equipment/turbomachinery and align with refinery operating philosophies.
• Rotary Equipment & Turbomachinery Reliability Leadership
  • Lead reliability input and validation for critical rotating assets (pumps, compressors, turbines, motors, gearboxes) focusing on common degradation/failure drivers (e.g., bearing/seal failures) and practical mitigation actions.
  • Support anomaly detection and root-cause analysis workflows for rotating equipment using predictive analytics approaches and tool-enabled insights
  • Integrate reliability recommendations into maintenance planning and execution processes (including CMMS integration where used) to improve reliability outcomes such as MTBF/MTTR improvement efforts
• Condition Monitoring & Vibration Analysis Leadership
  • Design and operationalize Condition Monitoring workflows for critical mechanical assets (pumps, compressors, turbines, etc.), including real-time monitoring of vibration/temperature/pressure signals to detect faults early and optimize performance. Embed vibration-based health indicators into predictive models (e.g., anomaly detection, incipient failure detection, remaining useful life signals) and ensure alerts are actionable for maintenance and reliability teams.
• Stakeholder Management & Client-Facing Delivery
  • Act as a trusted interface between maintenance/reliability teams, rotating equipment SMEs, and technical delivery teams; sustain credibility through practical understanding of refinery maintenance execution and reliability governance.
  • Lead structured feedback cycles (pilot deployments and phased rollouts) and translate feedback into clear backlog items/requirements for iterative improvement
  • Support proposal shaping and solution articulation for MENA opportunities aligned to maintenance transformation and predictive maintenance value cases.
• Governance, Quality & Assurance
  • Support definition of data quality standards, instrumentation/condition-data assumptions, validation checkpoints, and model monitoring controls for predictive maintenance solutions
  • Ensure solutions align with reliability engineering practices and contribute to playbooks, documentation, and governance artifacts for deployed predictive maintenance capabilities
  • Ensure solutions align with reliability engineering practices and contribute to playbooks, documentation, and governance artifacts for deployed predictive maintenance capabilities

Required Experience & Qualifications

• 8–10 years of downstream Oil & Gas experience with strong refinery maintenance & reliability depth, including predictive maintenance exposure and rotating equipment/turbomachinery familiarity.
• Proven experience articulating maintenance/reliability workflows in practice (work management, shutdown/turnaround interfaces, failure response, planning) and translating them into structured functional requirements.
• Strong communication and documentation skills; ability to translate maintenance and reliability concepts clearly to non-engineers and technical teams.
• Demonstrated cross-functional delivery experience spanning maintenance/reliability, operations, and digital teams.
• Fluency in English (mandatory).
• Engineering Degree in Chemical / Mechanical / Instrumentation / Petroleum disciplines
• MBA
• Experience from/with IOC environments and particularly Exxon Mobil / Shell / BP-type operating models.

Preferred / Nice-to-Have

• Exposure to digital maintenance transformation initiatives.
• Familiarity with predictive maintenance solution concepts such as digital twin-enabled maintenance visibility and proactive breakdown prevention
• Arabic language capability (optional).