Technical Lead Analysis and Data Analytics (m/f/d)

Job Description Summary

The Technical Lead Data Analytics Engineer is responsible for leading field data analytics and the development of software and tools used for gearbox and drivetrain evaluation. This role also owns the strategy and technical evaluation of commercial software used to support engineering analysis, assessment, and decision-making. The position applies advanced analytical and engineering expertise to convert field and technical data into actionable insights, improve evaluation methods, and support product reliability and performance improvements. The role works closely with engineering, service, quality, suppliers, and other internal stakeholders to strengthen technical understanding, drive corrective actions, and improve tool and software capabilities.

Job Description

Responsibilities :

• Lead field data analytics activities to assess gearbox and drivetrain performance, reliability, and failure trends

• Develop, enhance, and maintain software, tools, and analytical methods used for gearbox and drivetrain evaluation

• Define and drive the strategy for commercial software selection, evaluation, and application in support of engineering and analytics needs

• Evaluate commercial software solutions based on technical capability, fit for purpose, scalability, maintainability, and business value

• Analyze field, service, and engineering data to identify trends, anomalies, root causes, and opportunities for product improvement

• Support root cause analysis and the definition, execution, and tracking of corrective and preventive actions

• Collaborate with engineering, service, quality, manufacturing, and program teams to investigate technical issues and align on resolution paths

• Interface with suppliers and internal stakeholders to gather technical input, validate findings, and support issue resolution

• Communicate complex technical findings and recommendations to internal teams and leadership

• Ensure data integrity, traceability, consistency, and technical rigor across analytics outputs, software tools, and reporting

• Establish and share best practices for analytical methods, tool development, software evaluation, and technical documentation

• Provide technical guidance and mentoring to team members

• Contribute to reliability growth, continuous improvement, and lessons learned across the product line

• Bachelor's degree in Engineering, Mechanical Engineering, Data Analytics, Computer Science, or a related technical field

• Significant experience in field data analytics, engineering analytics, software/tool development, or a related technical discipline

• Strong technical knowledge of gearbox and drivetrain systems, performance behavior, and failure mechanisms

• Demonstrated experience leading technical problem-solving and cross-functional issue resolution

• Experience with software development, analytics platforms, engineering tools, dashboards, or technical assessment methods

• Experience evaluating commercial software solutions and making technical recommendations

• Strong analytical, communication, and stakeholder management skills

• Ability to assess technical information, challenge assumptions, and drive action-oriented outcomes

• Experience working in a matrixed, cross-functional environment

• Experience in wind turbine gearbox or drivetrain evaluation

• Familiarity with root cause analysis, corrective action processes, and reliability methods

• Experience developing or improving engineering tools, digital solutions, or technical platforms

• Proficiency in SQL, Python, Power BI, Tableau, MATLAB, or similar tools

• Experience with commercial software selection, benchmarking, or implementation

• Strong business acumen and understanding of performance, quality, reliability, and cost tradeoffs

• Ability to influence without authority and build consensus across teams

• Strong ownership, accountability, and continuous improvement mindset

• Providing advanced technical expertise and direction

• Working with a high degree of autonomy within established frameworks

• Influencing tools, methods, and technical approaches across teams

• Solving complex technical and analytical problems

• Collaborating across functions and with external suppliers to drive decisions and improvements