Asset Health Data Specialist

OW Ocean Winds; Madrid; Presencial; EUR 50.000 - 70.000; Jornada completa

Descripción de la vacante

A leading renewable energy company in Madrid seeks an Asset Health Data Specialist. The role involves leveraging data analytics to ensure optimal performance and sustainability of offshore wind assets. Responsibilities include developing data pipelines, applying predictive maintenance techniques, and collaborating with engineers to optimize asset performance. Ideal candidates should have a degree in engineering and strong experience in data engineering tools. Fluency in English is required.

Formación

• Proven experience in data engineering or analytics, preferably in energy or offshore wind sectors.
• Fluency in spoken and written English; proficiency in additional languages is valued.

Responsabilidades

• Support development and enhancement of data pipelines from various sources.
• Implement data models to monitor asset health and identify degradation.
• Apply predictive maintenance techniques to forecast failures.
• Develop algorithms for analyzing turbine component conditions.
• Collaborate with engineers to convert data insights into strategies.

Conocimientos

Data engineering tools (Python, SQL, Spark)

Predictive maintenance

Problem-solving skills

Attention to detail

Educación

Degree in relevant engineering discipline

Herramientas

SCADA systems

Condition-monitoring technologies

Cloud platforms (AWS, Azure)

Descripción del empleo

About the job

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 growing environment?

GENERAL DESCRIPTION

The Asset Health Data Specialist will be key to ensuring the optimal performance, reliability, and sustainability of offshore wind assets. They will leverage data analytics, engineering principles, and modern technology to monitor and assess wind turbine and infrastructure health. Working closely with the Lead O&M Data Engineer, they will help set up tools, data pipelines, and algorithms to improve asset performance, reduce downtime, and optimize maintenance through data-driven decisions. Collaboration with the Lead Performance Engineer is essential to provide a holistic view of asset status. The role requires effective communication with diverse stakeholders and the ability to present findings clearly.

MAIN ACCOUNTABILITIES

• Support development, maintenance, and enhancement of data pipelines from sources like SCADA, sensors, and Asset Integrity Monitoring Systems.
• Implement data models to monitor asset health, identify degradation, and detect early failure signs.
• Apply predictive maintenance techniques, including machine learning and statistical models, to forecast failures and optimize schedules.
• Develop algorithms to analyze the condition of turbine components such as blades, bearings, gearboxes, and electrical systems.
• Collaborate with O&M engineers and asset managers to translate data insights into actionable strategies.
• Assist in creating decision-support tools for maintenance prioritization and risk management.
• Create dashboards and reports communicating asset health, performance, and risks to technical and non-technical teams.
• Ensure data integrity and provide regular updates on asset health metrics.
• Participate in designing advanced analytics tools and systems for asset data processing.
• Research and implement new data-driven technologies like AI and IoT for monitoring and diagnostics.
• Ensure compliance with industry standards, certifications, and best practices related to asset management and data handling.
• Support regulatory reporting and audits by maintaining data accuracy and traceability.

ACADEMIC BACKGROUND AND PROFESSIONAL EXPERIENCE

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

REQUIRED KNOWLEDGE AND COMPETENCIES

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

LANGUAGES

• The working language is English; candidates must be fluent in spoken and written English. Proficiency in additional languages is valued.

SKILLS

• Willingness to learn and develop new technical skills.
• Flexibility in achieving objectives.
• Strong problem-solving skills with the ability to interpret complex datasets and provide insights.
• Attention to detail to ensure data accuracy and quality.
• Keen to take on responsibilities, collaborate as a team, and share knowledge.
• Ability to communicate technical information effectively to diverse audiences.

OTHER REQUIREMENTS

• Travel to project and OEM sites may be required.