PV Performance Analyst

Select Offshore; Madrid; Híbrido; EUR 40.000 - 60.000; Jornada completa

Descripción de la vacante

A leading company in the renewable energy sector is looking for a Performance Analyst to join their global team. The role focuses on performance diagnostics, evaluating KPIs, and optimizing solar PV and battery storage systems. Candidates should have hands-on experience with PV modeling software and strong Python skills. This opportunity offers a chance to impact sustainability in a flexible, supportive working environment.

Servicios

Flexible hybrid working

Generous time-off policies

Professional growth opportunities

Wellbeing support

Work-from-anywhere flexibility

Family-first policies

Formación

• Solid experience working with PV modeling software.
• Proven ability to analyze system performance data and energy KPIs.
• Strong command of Python for performance simulations and loss analysis.

Responsabilidades

• Evaluate key performance indicators (KPIs) and identify deviations.
• Analyze energy losses and implement solutions to boost asset performance.
• Develop and refine digital twin models for solar PV and battery systems.

Conocimientos

PV modeling software

Data analysis

Python

Performance simulations

Energy KPI analysis

Digital twins

Collaboration

Descripción del empleo

Performance Analyst – Renewable Energy (Open Location – Preference for Spain)

Location : Flexible across Europe (Madrid preferred)

Sector : Solar PV & Battery Storage | Renewable Energy Operations

We are supporting a well-established, international renewable energy producer in the search for a Performance Analyst to join their growing global operations team. With a strong pipeline of solar and hybrid energy assets, this company is deeply committed to long-term sustainability, innovation, and technical excellence.

This role is ideal for candidates who bring hands-on experience in PV system modelling and data analysis and who are excited to contribute to improving the performance of clean energy assets at scale.

The Opportunity

As a Performance Analyst, you'll be part of a cross-functional team working on the development and refinement of digital twin models that simulate solar PV and battery energy storage systems. Your primary focus will be on performance diagnostics—evaluating key performance indicators (KPIs), identifying deviations, analyzing energy losses, and implementing solutions to boost asset performance.

This position offers the chance to make a meaningful impact in the clean energy space while working in a supportive and flexible international environment.

Key Qualifications :

• Solid experience working with PV modeling software
• Proven ability to analyze system performance data and energy KPIs
• Strong command of Python , particularly for performance simulations and loss analysis
• Background or interest in digital twins and system optimization
• Excellent communication skills and ability to collaborate across departments

Note : Business language is English – CVs must be submitted in English.

Preferred Profile :

• Based in Spain , to allow for closer collaboration with the technical operations team
• Previous experience in the solar PV or energy storage sector highly desirable

Why Join?

• Work with a company at the forefront of the global energy transition
• Contribute to high-impact projects involving real-time performance optimization of renewable assets
• Flexible hybrid working with generous time-off policies (including a 'work away scheme')
• Professional growth opportunities through a structured internal academy
• Inclusive, international culture and strong internal mobility
• Attractive benefits including wellbeing support, work-from-anywhere flexibility, and family-first policies

If you're a curious, analytical professional with a passion for renewable energy and a knack for solving performance challenges, we'd love to connect with you.

Interested or want to learn more?

Please reach out directly to discuss the role in more detail or refer qualified contacts who may be a good fit.