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.
QualificationsRequired Education, Skills & Experience- Bachelor's degree in Information Systems, Data Analytics, Computer Science, Engineering, or a related field.
- 3 - 8 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.
