Global Reliability SME, Electrical Assets

About the role

Heidelberg Materials is recruiting a Global Reliability SME for Electrical Assets in its Digital Hub in Wrocław, Poland. You will act as a central technical expert for electrical equipment reliability and predictive maintenance, working with plant teams, maintenance specialists, digital experts and external partners to improve asset performance, equipment availability and operational excellence worldwide.

Key responsibilities

• Define and support predictive maintenance use cases for critical electrical assets, analyze failure modes and reliability risks, and conduct criticality assessments, root cause analyses and reliability improvement initiatives.
• Translate electrical failure mechanisms into monitoring requirements and maintenance recommendations.
• Support implementation and optimization of C3.ai Reliability and other asset health platforms, validate asset structures, sensor mappings and data quality, and analyze trends and alerts.
• Collaborate with plant maintenance, automation, IT/OT and reliability teams, investigate reliability alerts and recommend corrective and preventive actions.
• Support troubleshooting of recurring electrical equipment issues.
• Develop global standards, guidelines and failure mode libraries, and train and coach maintenance and electrical teams in asset health interpretation and predictive maintenance.

Required profile

• Degree in Electrical Engineering, Automation Engineering, Maintenance Engineering or a related field.
• Minimum 5 years of experience in electrical maintenance, reliability engineering or asset management within heavy industry.
• Fluent English.
• Preferred: experience with motors, VFDs, transformers, switchgear and power distribution; background in cement, mining, aggregates, power generation or other heavy industry; experience with predictive maintenance platforms; knowledge of OT systems, industrial historians, SCADA or electrical protection systems; reliability or electrical safety certifications.

Required skills

• Knowledge of maintenance management processes and CMMS/SAP PM environments.
• Experience interpreting operational and condition-monitoring data.
• Preferred: familiarity with C3.ai Reliability, DALOG, Machine Sentry or similar solutions.

What we offer

• Contribution to a global reliability and predictive maintenance transformation, with international cooperation and about 25% travel time.
• Hybrid working model.
• Professional development opportunities and a culture of safety, continuous improvement and innovation.
• Benefits including private medical care, MultiSport membership, holiday and children's summer camp allowances, and support for cultural and sports activities.