Power Generation Engineer

Requisition ID:  95974 

Florida Power & Light Company is the largest electric utility in the U.S., providing reliable energy to nearly 12 million Floridians. With one of the nation’s most fuel-efficient, cost-effective power generation fleets and industry-leading reliability, we’re redefining what’s possible in energy. Want to be part of something powerful? Join our outstanding team and help shape the future of energy.

Position Specific Description

The PGD Fossil Reliability Engineer leads reliability improvement initiatives across the company’s fossil generation fleet, with a significant emphasis on predictive analytics, condition-based maintenance, and data-driven asset management.

This role identifies emerging equipment risks, predicts failures, optimizes maintenance strategies, and improves unit availability, reliability, and cost performance by developing and operationalize predictive models using plant historian, maintenance, inspection, operational, and condition-monitoring data.

The successful candidate will partner with plant engineering, operations, maintenance, information technology, data science, and leadership teams to convert asset data into actionable recommendations.

Employees in this role have responsibility for interpreting, organizing, executing, and coordinating assignments.This involves exploration of subject area, definition of scope, selection of areas for investigation, and development of novel concepts.

Key Responsibilities

• Predictive Analytics and Equipment Health
• Lead the development, validation, deployment, and continuous improvement of predictive analytics models for critical fossil generation assets.
• Analyze time-series data from plant historians, control systems, maintenance systems, and conditionmonitoring platforms to identify abnormal operating patterns and early indicators of equipment degradation.
• Develop equipment health indicators, anomaly-detection models, failure-risk scores, and remaining-useful-life estimates.
• Apply statistical, engineering, and machine-learning techniques to predict failures, reduce unplanned outages, and improve maintenance timing.
• Perform data preparation, cleansing, feature engineering, trend analysis, and model validation using operational and maintenance data.
• Establish appropriate model thresholds, alert logic, confidence levels, and escalation processes while minimizing false positives and non-actionable alarms.
• Monitor predictive-model performance and update models as equipment conditions, operating profiles, and maintenance strategies change.
• Translate analytical findings into clear equipment-risk assessments and prioritized maintenance recommendations.
• Integrate predictive insights into work-management, outage-planning, and asset-management processes.
• Develop dashboards and automated reporting that communicate equipment health, risk exposure, emerging failure modes, and recommended actions.
• Support the development of digital twins, fleet benchmarking, and advanced asset-performance-monitoring capabilities.
• Reliability Engineering
• Lead reliability-centered maintenance analyses for critical systems and equipment.
• Develop and maintain asset criticality rankings, failure-mode libraries, equipment health strategies, and preventive and predictive maintenance programs.
• Perform root-cause failure analyses for significant equipment failures, forced outages, derates, and recurring maintenance issues.
• Facilitate failure modes and effects analysis, fault-tree analysis, Weibull analysis, bad-actor analysis, and other structured reliability evaluations.
• Identify opportunities to transition from time-based maintenance to condition-based or risk-based maintenance.
• Evaluate equipment performance and recommend design changes, operating changes, inspection strategies, or maintenance improvements.
• Review maintenance history, failure patterns, inspection findings, and operational data to identify chronic reliability issues.
• Provide technical support for major outages, equipment overhauls, plant modifications, and capitalimprovement projects.
• Plans and develops engineering projects concerned with unique or controversial complexities which have important impact on major company programs 
• Acts as technical liaison to individuals within and outside the organization with responsibility to act independently regarding technical matters pertaining to individual's field 
• Completes assignments given in broad terms concerning general objectives and limitations 
• Performs other job-related duties as assigned.

The ideal candidate would have the following:

• Bachelor’s degree in mechanical engineering, electrical engineering, chemical engineering, reliability engineering, data science, or a closely related technical field.
• 2+ years of engineering experience in power generation, heavy industrial operations, asset management, reliability, maintenance, or equipment performance.
• Experience analyzing large operational or time-series datasets.
• Working knowledge of statistical modeling, anomaly detection, regression, classification, forecasting, or machine-learning methods.
• Ability to translate analytical outputs into practical engineering and maintenance recommendations.
• Strong technical writing, presentation, facilitation, and stakeholder-management skills.
• Certified Maintenance and Reliability Professional, Certified Reliability Engineer, or similar certification.
• Experience with one or more of the following:
• Python, R, SQL, MATLAB, or similar analytical tools
• Power BI, Tableau, or other visualization platforms
• PI System or another industrial process historian
• SAP, Maximo, or another computerized maintenance management system
• Asset-performance-management or predictive-maintenance platforms
• Cloud-based data and analytics environments
• Experience deploying analytical models into production or operational workflows.
• Travel: Approximately 10%–20%, primarily to generation facilities