Analista De Datos ofertas em Espanha

OW a controlled 50 / 50 joint venture between EDP and Engie is looking for a proactive and analytical Asset Health Data Specialist.

Are you willing to join a passionate and high performing team, in a cross-cultural, fast-paced, and strongly grOWing environment?

The Asset Health Data Specialist will be integral to ensuring the optimal performance, reliability, and long-term sustainability of offshore wind assets. By leveraging data analytics, engineering principles, and modern technology, they will monitor and assess the health of wind turbines and associated infrastructure. The Asset Health Data Specialist will work closely with the Lead O&M Data Engineer to setup the tools, data pipelines and algorithms to improve asset performance, reduce downtime, and optimize maintenance strategies through proactive, data-driven decision-making. In collaboration with the Lead Performance Engineer, they must provide a holistic view of the performance and status of the assets. They must be comfortable working with a wide range of stakeholders and functional teams and being able to communicate results and findings in an adapted manner to the audience.

• Support the development, maintenance and enhancement of data pipelines from various data sources, including SCADA, standalone sensors and Asset Integrity Monitoring Systems.
• Implement data models to monitor the health of offshore wind assets, identifying degradation patterns, and detecting early signs of component failures.
• Apply predictive maintenance techniques (e.g., machine learning, statistical models) to forecast potential failures and optimize maintenance schedules.
• Develop algorithms and tools to analyse the condition of wind turbine components such as blades, bearings, gearboxes, and electrical systems.
• Work closely with O&M engineers, asset managers, and other stakeholders to translate data insights into actionable strategies.
• Assist in developing decision-support tools that help the O&M team prioritize maintenance tasks and manage asset risks effectively.
• Create dashboards and reports that communicate asset health, operational performance, and risk levels to technical and non-technical stakeholders.
• Ensure data integrity and consistency across platforms and provide regular updates on asset health metrics.
• Participate in the design and development of advanced analytics tools and systems that streamline the processing and analysis of asset health data.
• Research and support the implementation of new data-driven technologies (AI, IoT) to enhance condition monitoring and diagnostics.
• Ensure compliance with industry standards, certifications, and best practices related to asset management and data handling within the offshore wind industry.
• Support regulatory reporting and audits by ensuring data accuracy and traceability.

• A degree in a relevant engineering discipline (e.g., Industrial Engineering, Energy Engineering, Electrical Engineering, Naval Engineering, Mechanical Engineering or equivalent) is required.
• Proven experience in data engineering, analytics, or asset health management, preferably in the energy or offshore wind industry.

• Strong knowledge of data engineering tools (e.g. : Python, SQL, Spark) and platforms (AWS, Azure, etc.).
• Experience with SCADA systems, CMS, and other condition-monitoring technologies used in wind farms.
• Proficiency in predictive maintenance techniques, failure mode analysis, and machine learning models.
• Familiarity with offshore wind turbine systems and components is highly desirable.
• Familiarity with substructures and HV transmission assets is a plus.

• The company has an international team of employees, and the working language is English. Candidates need to be fluent in English both spoken and written. Proficiency in other languages will be valued.

• Willingness to learn and develop new technical skills.
• Flexibility to work towards objectives.
• Excellent problem-solving skills with the ability to interpret complex datasets and provide actionable insights.
• Attention to detail, ensuring the accuracy and quality of asset health data and analysis.
• Keen on taking new responsibilities, working as a team, and sharing knowledge.
• Ability to deliver technical explanations adapted to the target audience.

• Travel to project and OEM sites may be required.

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