Job Description Summary

The Senior Engineer – Fleet Monitoring, Pitch Bearing is responsible for developing and executing the fleet monitoring strategy for pitch bearing components across the installed base. This role combines deep technical expertise in pitch bearing diagnostics and condition monitoring with a broader strategic responsibility to support component decision-making, repair versus replace analysis, and the development of new monitoring and maintenance capabilities. The engineer will serve as the subject matter expert for pitch bearing health across the fleet and will partner with engineering, services, and commercial teams to drive reliability, availability, and cost-effective outcomes for customers and the business.

Job Description

Roles and Responsibilities

Fleet Monitoring and Diagnostics

• Develop, own, and continuously improve the fleet monitoring strategy for pitch bearing components across the installed base.
• Monitor pitch bearing performance indicators and operational data to identify emerging issues, degradation trends, and opportunities to improve reliability and maintenance outcomes.
• Define and refine detection methods, alert logic, and diagnostic workflows specific to pitch bearing condition and failure modes.
• Lead root cause investigations for pitch bearing failures and develop data-driven recommendations to resolve fleet and customer issues.
• Support outage management, service bulletin implementation, and fleet configuration activities related to pitch bearing components.
• Maintain fleet data integrity and configuration records relevant to pitch bearing health and history.

Detection and Monitoring Capability Development

• Identify gaps in current pitch bearing monitoring coverage and drive development of new or improved detection methods.
• Partner with digital, analytics, and engineering teams to define use cases and requirements for advanced pitch bearing monitoring, anomaly detection, and prognostics.
• Support validation and deployment of new monitoring algorithms, models, or tools specific to pitch bearing health assessment.
• Drive continuous improvement in data quality, alert effectiveness, and diagnostic accuracy for pitch bearing monitoring.

Component Strategy and Decision Support

• Serve as the technical subject matter expert on pitch bearing health to support broader GE Vernova teams in component strategy decisions.
• Provide data-driven analysis and recommendations to inform repair versus replace decisions at the fleet and individual asset level.
• Support assessment of whether new up-tower repair capabilities should be developed, providing technical input on feasibility, fleet need, and value case.
• Collaborate with engineering, services, supply chain, and commercial teams to align monitoring insights with component lifecycle strategy and investment decisions.
• Communicate fleet health trends, risk assessments, and strategic recommendations clearly to stakeholders across functions and levels of the organization.

Team and Cross-Functional Collaboration

• Serve as a technical resource and best-practice leader for the fleet monitoring team on pitch bearing topics.
• Support development of less experienced engineers through knowledge sharing, documentation, and mentoring.
• Lead or support projects of moderate to high scope and complexity related to pitch bearing performance, monitoring effectiveness, component strategy, and capability development.

Required Qualifications

• Bachelor's Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with advanced experience.
• Minimum 12 years wind industry expertise

Desired Characteristics

• Strong experience in fleet monitoring, diagnostics, reliability, or component engineering — experience with pitch bearings, main bearings, or rotating mechanical components strongly preferred.
• Familiarity with bearing failure modes, degradation mechanisms, condition monitoring techniques, and maintenance strategies.
• Demonstrated ability to develop or improve monitoring strategies, detection methods, or diagnostic workflows.
• Experience supporting component strategy decisions including repair versus replace analysis, lifecycle assessments, or maintenance optimization.
• Strong analytical and problem-solving skills with demonstrated ability to analyze and resolve complex technical issues.
• Experience working with digital tools, data analytics, or AI-enabled technologies to improve monitoring or diagnostic outcomes.
• Strong oral and written communication skills with the ability to present technical findings and strategic recommendations to diverse audiences.