Job Description Summary

The Senior Engineer, Blades Fleet Engineering, will lead proactive fleet performance management for the GE Vernova Wind Blade fleet. You will be responsible for driving sustained product improvement throughout our global fleet, shifting from reactive troubleshooting to a proactive, data-led reliability model. You will develop and implement quality initiatives and drive closed-loop lessons learned across the product lifecycle.

Job Description

Essential Responsibilities

• Predictive Analytics Integration: Leverage fleet-wide data across manufacturing, projects, and services platforms alongside AI-driven diagnostic tools to identify early-stage blade degradation, enabling proactive maintenance.

• Data-Driven RCA Methodology: Utilize machine learning algorithms to process large-scale historical failure data, accelerating root cause identification and validating the efficacy of corrective actions through statistical modeling.

• Automated Quality Reporting: Implement and maintain automated data visualization dashboards to monitor Blade fleet quality KPIs, ensuring real-time visibility into emerging trends for leadership and stakeholders.

• Blade Master file: Create and maintain Blade master file database for all GE Vernova Wind blades integrating existing database from Production, Installation and Service

• Proactive Fleet Management: Collaborate with blade fleet performance teams to identify and address emerging technical issues before they impact fleet availability.

• Data Infrastructure Ownership: Drive continuous improvements in fleet data quality, data completeness, and the underlying infrastructure supporting our analytics.

• Problem-Solving Leadership: Facilitate RCA Kaizens to achieve faster, more robust resolutions. Own and support action items derived from Quality PSR countermeasures.

• Process Implementation: Drive the application of structured problem-solving tools and methods throughout the entire RCA process.

• Cross-Functional Partnership: Seamlessly collaborate with fleet performance management, manufacturing, projects, services, and digital technology teams to ensure a unified approach to fleet reliability.

• Support similar initiatives driven by cross functional teams such as being focal point within Blade Fleet engineering for Blade FAX and Turbine monitoring platforms

• Team Work: Proven ability to work effectively in a globally focused, culturally diverse, and highly matrixed organizational environment.

Qualifications & Requirements

• Education: Bachelor’s degree in Engineering (STEM-based).

• Experience: 7+ years of professional experience in wind turbine blade engineering and/or product management.

• Travel: Ability to travel globally approximately 10% of the time.

Desired Characteristics

• Data Literacy & Tooling: Proficiency in data analysis and visualization software (e.g., SQL, Python, R, MATLAB, PowerBI, or Tableau) with experience interpreting large, complex datasets for technical decision-making.

• AI/ML Expertise: Understanding of how AI and predictive maintenance models apply to mechanical structures and wind turbine blade health monitoring.

• Statistical Analysis: Strong foundation in statistical quality control (SQC) and reliability engineering metrics (e.g., Weibull analysis, reliability growth modeling).

• Risk Mitigation: Experience developing comprehensive action plans to mitigate fleet risks arising from technical issues.

• Quality Systems: Familiarity with quality systems, procedure development, technical training, and execution.

• Communication: Experience with high-level customer communications regarding quality and RCA outcomes.

• Lean Methodologies: Proficiency in Lean tools, coaching, and facilitating Kaizen events.

Additional Information