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Asset Management Data Analyst

Cleco Corporate Holdings LLC
United States, Louisiana, Pineville
Mar 30, 2026

At Cleco, we're not just poweringlives-we're powering a cleaner, smarter future for Louisiana.With bold investments in innovativeenergysolutions, we're transforminghow we power ourcommunities: smarter, cleaner, and more sustainable.This is a long-term commitmentto our people and our communities because our future-and the future of generations to come-depends on it. If you're ready to make an impact where it matters most, join us at Cleco-where we're Energizing Your Tomorrow.

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.

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