LEAD PERFORMANCE OPTIMISATION ENGINEER (F/M/D) | IGNITIS RENEWABLES
LEAD PERFORMANCE OPTIMISATION ENGINEER (F/M/D) | IGNITIS RENEWABLES
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Job Description
We are currently looking for a new colleague to join the Asset Performance and Optimization Team of the Ignitis Renewables where youll lead the Performance Optimisation function to ensure our renewable energy asset portfolio operates at peak efficiency driving both technical and commercial performance. If that speaks to you wed be happy to welcome you to our team!
Take YOUR part in #EnergySmart!
You will contribute to green and secure energy ecosystem creation by:
- Leading and managing a team of Performance Optimisation Engineers ensuring effective performance and resource management professional growth and high employee satisfaction and retention
- Establishing managing and continuously improving the structure and processes of the Performance Optimisation function ensuring seamless collaboration across internal teams departments and external partners
- Contributing to the ongoing development and implementation of the O&M and Technical Asset Management strategy
- Ensuring timely reliable and high-quality execution of performance optimisation projects
- Overseeing portfolio-wide reporting on asset health and performance metrics while proactively addressing evolving reporting needs for internal and external stakeholders
- Driving the development and improvement of machine learning models for forecasting asset deterioration condition monitoring and fault prediction
- Conducting ad-hoc optimisation and engineering studies delivering actionable recommendations
- Identifying and evaluating performance improvement opportunities across the renewable energy asset portfolio including market research upgrade assessments and business case preparation.
Qualifications :
- An academic degree in Engineering Physics Data Science Machine Learning or a related field
- 3 years of experience in engineering or a similar role ideally within the renewable energy sector or O&M provider organisations
- Proven experience in leading and managing engineering teams including performance management professional development and ensuring team satisfaction
- Proficiency in advanced statistical methods and machine learning techniques with the ability to develop or improve analytical tools for large-scale data analysis
- Strong engineering background with a deep understanding of engineering systems and at least a basic knowledge of renewable energy systems
- Proficiency in research and evaluation of asset upgrade options including preparing business cases and assessing technical and commercial viability
- Skilled in data visualization with experience using tools like Power BI to clearly communicate analytical findings
- Advanced user of MS Office
- Fluency in English and strong communication skills to align with both team members and management.
Additional Information :
- To take part in an unfolding energy transformation process to create a 100% green and secure energy ecosystem for both current and future generations
- International team that is working on dynamic renewable energy projects
- A hybrid work model (32) and flexible working hours
- Extensive learning and qualification enhancement programs
- Attention to physical and emotional health: wellness mentor initiatives and psychological support etc.
- Additional paid days for health improvement short-term illness volunteering and accumulated work experience
- A package of additional benefits to choose from: pension accumulation health insurance or another benefit from the selectable benefits list in the MELP application.
Join a growing and increasingly international team of energy smart people united by a common purpose. We all play our part in creating a 100% green and secure energy ecosystem for current and future generations.
As we pursue our strategic goals to increase gender balance in Ignitis Group we are indicating f/m/d next to job titles meaning we welcome candidates of all genders female male or diverse.
Ignitis Group is committed to a policy of equal employment opportunity and does not discriminate against race religion gender sexual orientation or gender identity age disability or other personal traits unrelated to work obligations.
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
