Maintenance Expert

Overview

We are searching for a GLOBAL MAINTENANCE EXPERT to support the predictive maintenance projects for a client in the pharmaceutical sector in the region of Brussels.

Responsibilities

Day to day tasks:Define, maintain and communicate the global Predictive Maintenance strategy, roadmap and governance model in alignment with Asset Management and Reliability objectives.
Develop and own the Predictive Maintenance Playbook, covering use-case selection, asset eligibility, monitoring strategies, alarm governance, operating models and lifecycle requirements.
Establish global technical standards and minimum requirements for condition-monitoring technologies, data acquisition, connectivity, analytics, diagnostics and integration with maintenance processes.
Build a risk-based methodology to prioritize assets and select the appropriate predictive techniques based on asset criticality, failure modes, detectability, business impact and value potential.
Provide expert guidance on vibration analysis, ultrasound, thermography, oil and lubricant analysis, motor and electrical condition monitoring, process-parameter analytics and other relevant predictive techniques.
Assess AI, machine learning, Asset Performance Management, digital twin and advanced analytics solutions for technical relevance, scalability, explainability and sustainable business value.
Lead technical evaluations, Proofs of Concept and qualification activities for predictive-maintenance technologies in collaboration with site, project, Quality, EHS, Digital Technology and Procurement stakeholders.
Define functional and data requirements for predictive-maintenance capabilities in new assets and major capital projects through Reliability by Design and Asset Ready for Maintenance processes.
Support the integration of predictive findings into CMMS/EAM workflows, work management, maintenance plans, RCM/FMECA outputs, asset strategies and continuous-improvement processes.
Combine engineering expertise with historians, CMMS/EAM, APM, data landscapes, data warehouses, IoT solutions and analytics data to generate actionable asset-health insights.
Perform or support complex diagnostic investigations and translate condition, process and reliability data into clear technical recommendations and risk-based actions.
Develop business cases and value-tracking methodologies covering avoided failures, risk reduction, equipment availability, maintenance productivity, lifecycle cost and sustainable resource use.
Define and monitor global predictive-maintenance KPIs and asset-health indicators and contribute to dashboards, management reviews and cross-site performance comparisons.
Build and coordinate a global network of predictive-maintenance practitioners and external experts, sharing lessons learned, standards, reference architectures and proven practices.
Develop competency matrices, training content and coaching approaches for Reliability, Maintenance and Engineering teams.
Monitor external technology developments and pharmaceutical-industry practices and recommend innovations that strengthen reliability, compliance and lifecycle performance.
Provide technical oversight of strategic suppliers, including competency expectations, deliverable quality, data ownership, service performance and standardization opportunities.
Ensure that solutions and resulting decisions are documented in accordance with applicable cGxP, data-integrity, Quality, EHS, cybersecurity and internal procedural requirements.
Spend approximately half of the time on hands-on technical work, including designing predictive-maintenance processes and defining interactions with current and future systems.
Spend approximately half of the time on stakeholder engagement, reporting, presentations and communicating complex or highly technical ideas in a clear and accessible way.
Create visibility and engagement around predictive maintenance, address potential resistance to new approaches and influence stakeholders without hierarchical authority.
Work with a high level of autonomy, proactively identify and connect with the appropriate stakeholders and integrate rapidly into the organization.
Focus on technical delivery and reporting rather than on financial project management.
Qualifications

Experience in the position Minimum 8 years of relevant experience in reliability, maintenance engineering, condition monitoring, asset management or industrial analytics.
Candidates with 6-8 years of experience may be considered only if they already demonstrate strong, directly applicable expertise and can operate independently without requiring technical upskilling in predictive maintenance.
Candidates with significantly more experie