Asset Management Data Analyst

Cleco is seeking an Asset Management Data Analyst II to connect plant operational signals with commercial context and turn that data into practical analytics for generation asset performance. This role focuses on building and governing analytics solutions that support decision-making through dashboards, time series analysis, workflow optimization, and maintenance-focused insights.

Based onsite in Pineville, LA, the analyst will partner across Asset Management, Generation Operations, Data Analytics/Data Science, and IT to integrate industrial time series from operational systems into business processes and enterprise data initiatives.

What you’ll do

• Help drive a corporate culture centered on transparency, integrity, safety, environmental responsibility, employee development, sense of belonging, customer service, and operational excellence.
• Accelerate development and deployment of data analytics that support business decisions.
• Gather and analyze operational and commercial data to uncover trends, patterns, and actionable insights.
• Monitor and report on progress for analytics and data management initiatives.
• Apply industry best practices to continuously improve asset performance through analytics.
• Collaborate with generation plant teams to understand data requirements, emphasizing time series data from operational systems and integration with business data.
• Build and maintain dashboards, reports, and visualizations using BI tools such as Power BI and Tableau.
• Use time series analysis to identify trends, anomalies, and opportunities to optimize equipment performance and reliability.
• Model asset health metrics and KPIs that inform predictive maintenance and lifecycle strategies.
• Support data quality by ensuring time series data is accurate, reliable, and consistent.
• Design and maintain data workflows and pipelines, with an emphasis on real-time or near-real-time availability of time series data.
• Coordinate with enterprise data teams to align local plant data strategies with broader data governance and architecture initiatives.
• Assist in defining an AI/ML roadmap for asset management, including anomaly detection approaches and digital twin simulations.
• Architect and leverage an Azure-based data analytics platform to support scalable model development and deployment.
• Participate in development and optimization of analytics processes, including integration of operational and business data.

Required qualifications

• Bachelor’s degree in Information Systems, Data Analytics, Computer Science, Engineering, or a related field.
• 3 to 8 years of experience in a data analytics or business intelligence role (3+ years required; 3–8 preferred).
• Hands-on experience with BI tools (for example, Power BI, Tableau, Qlik) 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 when combining operational and business datasets.
• Strong analytical and problem-solving skills.
• Strong experience in generation / commercial operations.
• Proficiency in data visualization tools (for example, Power BI) to create dashboards and reports.
• Knowledge of data management practices and tools.
• Excellent communication and presentation skills, with the ability to collaborate across cross-functional teams.
• Strong organizational and project management skills.
• Understanding of asset health metrics, predictive maintenance strategies, and how they improve operational efficiency.
• Familiarity with enterprise 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 (for example, Azure Databricks, Azure Machine Learning, Azure Data Lake) or similar cloud platforms (AWS/GCP).
• Progression to this level is restricted based on critical individual capabilities and business requirements, and must be supported by market survey data.

Technologies you may use

• Power BI, Tableau, Qlik
• SQL
• SCADA, IoT
• Azure, Azure Databricks, Azure Machine Learning, Azure Data Lake
• AWS, GCP

Certifications

• Relevant certifications (for example, 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/Business: Analytical skills; Organizational skills; Strategic Planning; Data Collection and Analysis; Presentation Skills; Business Intelligence skills