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The Asset Management Data Analyst II is an experienced professional responsible for integrating plant operational and commercial data & analytics into business processes to optimize generation asset performance. This position will leverage analytical skills, business intelligence expertise, and operational & commercial experience to deliver insights and data solutions that enhance operational efficiency, asset health, maintenance optimization, and commercial performance through various means including data visualization dashboards. This role will require a deep understanding of time series data, data governance & integrity strategies, its integration with business data, and its application in monitoring plant performance and supporting maintenance decision-making. This position bridges the gap between Asset Management, Generation Operations, Generation Services, Energy Operations, Corporate Data Analytics/Data Science, and IT to meet business objectives.

Key Responsibilities

• Champions a corporate culture that emphasizes transparency, integrity, safety, environmental responsibility, employee development, sense of belonging, customer service, and operational excellence.
• Accelerate the development and implementation of data analytics to support business decision-making.
• Gather and analyze operational and commercial data to identify trends, patterns, and insights.
• Monitor and report on the progress of analytics and data management initiatives.
• Stay up-to-date with industry trends and best practices in data analysis to continuously improve asset performance
• Collaborate with generation plant teams to understand data requirements, focusing on time series data from operational systems and integrating it with business data for comprehensive insights.
• Develop and maintain dashboards, reports, and visualizations using BI tools (e.g., Power BI, Tableau) to support operational performance, asset health monitoring, and maintenance strategy development.
• Analyze time series data to identify trends, anomalies, and opportunities for optimizing equipment performance and improving reliability.
• Work with plant teams to model asset health metrics and KPIs that inform predictive maintenance and lifecycle strategies.
• Support data quality initiatives by ensuring time series data is accurate, reliable, and consistent.
• Participate in the development and optimization of analytics processes, including the integration of operational and business data.
• Design and maintain data workflows and pipelines, with a focus on ensuring real-time or near-real-time availability of time series data.
• Collaborate with enterprise data teams to align local plant data strategies with broader enterprise initiatives, including data governance and architecture.
• Assist in defining roadmap for AI/ML in asset management including anomaly detection methods and digital twin simulations
• Architect and utilize Azure-based data analytics platform for scalable model development and deployment.

Qualifications

RequiredEducation, Skills & Experience

• Bachelor's degree in Information Systems, Data Analytics, Computer Science, Engineering, or a related field.
• 3 - 5 years of experience in a data analytics or business intelligence role preferred.
• Hands-on experience with BI tools (e.g., Power BI, Tableau, Qlik, etc.) and proficiency in SQL.
• Experience working with time series data from SCADA systems, IoT devices, or other industrial data sources.
• Experience in data integration and workflow optimization, particularly in combining operational and business datasets.
• Strong analytical and problem-solving skills.
• Strong experience in generation / commercial operations.
• Proficiency in data visualization tools (e.g., Power BI) to create dashboards and reports.
• Knowledge of data management practices and tools.
• Excellent communication and presentation skills.
• Ability to work collaboratively with cross-functional teams.
• Strong organizational and project management skills.
• Understanding of asset health metrics, predictive maintenance strategies, and their role in enhancing operational efficiency.
• Familiarity with enterprise data concepts such as data governance, data quality, and data architecture is a strong plus.
• Ability to translate complex data into insights that support asset health management and maintenance strategies.
• Experience with Azure data science and big data services (such as Azure Databricks, Azure Machine Learning, Azure Data Lake) or similar cloud platforms (AWS/GCP)
• Progression to this level is strictly restricted based on critical individual capabilities and business requirements; must be supported by market survey data

Licenses and Certifications

• Relevant certifications (e.g., Certified Business Analysis Professional (CBAP), Power BI Data Analyst Associate Certification) are a plus but not required.

Key Competencies

BEHAVIORAL

• Building Partnerships
• Leading Teams
• Business Acumen
• Communication
• Courage
• Building Self-Insight
• Driving for Results
• Energizing the Organization
• Driving Execution
• Building Trusting Relationships
• Driving Innovation
• Planning and Organizing
• Safety
• Establishing Strategic Direction

TECHNICAL

• Analytical skills
• Organizational skills
• Strategic Planning
• Data Collection and Analysis
• Presentation Skills
• Business Intelligence skills

May perform other duties as assigned.

Salary dependent on experience, skills, education, and training.