Asset Management Data Analyst

Cleco•Pineville, LA

3d•Onsite

About The Position

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.

Requirements

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

Nice To Haves

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

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.