Senior Reliability & Predictive maintenance Engineer

• Define and maintain technical frameworks for reliability, predictive maintenance, and health monitoring for solar, wind,and BESS assets (asset physics, failure mechanisms, and operational behavior), ensuring consistency and robustness across technologies.
• Translate the expertise into digital specifications, by defining reliability and health requirements (KPIs, degradation indicators, failure signatures, predictive signals) based on deep understanding of equipment design, operating conditions, and field feedback.
• Design, develop, and validate analytical models and algorithms leveraging asset physics and data science techniques, including failure mode detection, degradation modeling, remaining useful life estimation, and automated diagnostics.
• Drive advanced analytics use cases from an engineering stand point, ensuring that models and algorithms remain explainable, relevant for operations, and aligned with real asset behavior.
• Act as a technical interface with digital, IT, and data teams, ensuring that engineering assumptions, analytical needs and data quality constraints are correctly understood.
• Contribute to reliability and lifetime extension strategies by converting field experience, failure analyses, and model outputs into technical recommendations, standards, and design or operating improvements.
• Capitalise and structure knowledge through documentation (methodologies, models, data structures, architectures,lessons learned, best practices) to ensure long‑term maintainability, traceability, and reuse of developed solutions.
• Provide expert support and mentoring on reliability engineering, predictive maintenance methods, and modeling approaches to project teams and junior engineers, when required (without line or functional management responsibility).