Staff Analytics Engineer - Wind Fleet Data & Analytics

About the role

GE Vernova is looking for an experienced Staff Analytics Engineer to join its Wind Engineering FPM Fleet Data & Analytics team in Barcelona. The role builds scalable data and analytics solutions that support wind turbine reliability, fleet performance, engineering investigations and operational decisions, and delivers reusable analytics that grow the GE Vernova Wind Services portfolio. It works across SCADA, condition-based monitoring systems, turbine and sensor data, operational systems and enterprise data.

Key responsibilities

• Work with Analytics Engineers and Data Scientists to analyse equipment operation and failure modes using process environment, equipment operation and real-time sensor data.
• Design and build analytic packages: complete templates for a class of equipment including semantic data models, tag models, component groupings, failure indication logic and orchestration of physics-based, mathematical, statistical or machine learning techniques.
• Create derivative analytics for equipment variants, incorporate field feedback, maintain the analytic library and catalogue, and write functional documentation for Field Services teams.
• Gather end-user requirements, support product engineering on new solutions, and act as the communications hub and source of truth for analytics in the field.
• Support gate discussions, partner and cross-business collaboration, and present portfolio capabilities to customers and user groups.
• Manage Analytic Blueprint Packages, promote repeatability in solution architectures and foster innovation and agility.

Required profile

• Bachelor's degree in computer science or a STEM major with advanced experience.
• Good understanding of basic wind turbine equipment, reliability and failure causes, and ability to work with domain experts on failure modes and KPIs.
• Experience designing, deploying or operating applications and infrastructure in public or private cloud environments.
• Strong customer mindset, business acumen and ability to bridge research and solution design.

Required skills

• Proven experience with non-parametric machine learning algorithms or heuristics.
• Analytics software packages, open-source scripting and data analysis tools such as Python.
• Strong SQL and database expertise.
• Systems Development Life Cycle (SDLC) methodology.