Solar Performance Engineer – Asset Operations & Maintenance

Posted 2hrs ago

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Job Description

Solar Performance Engineer at Pivot Energy analyzing data for optimal solar energy production and efficiency. Collaborating with asset managers and technicians for performance improvement in operations and maintenance.

Responsibilities:

  • Performance Monitoring & Diagnostics: Monitor real-time and historical plant data to identify underperformance related to system alerts, equipment efficiency, AC and DC health, including but not limited to inverter efficiency, tracker misalignment, or string-level anomalies.
  • System Optimization: Identify inefficiencies and develop strategies to improve energy yield and system availability.
  • Troubleshooting: Diagnose and resolve technical issues affecting system performance, grid stability, and control systems. Root Cause Analysis (RCA): Lead technical investigations into equipment failures and outage events. Move beyond "what" happened to "why" by correlating meteorological data with electrical output.
  • Data Automation: Develop and maintain Python/R scripts or SQL queries to automate the ingestion and cleaning of DAS/SCADA data, replacing manual spreadsheet workflows.
  • Advanced Modeling: Use PVsyst and DAS modeling logic to compare actual vs. expected energy production, adjusting for degradation and weather variance and system loss identification.
  • Action Liaison: Translate complex data findings into "Action Reports." You will tell the asset managers and field technicians which specific components to test, reducing "truck roll" costs and mean time to repair (MTTR).
  • Contractual Compliance: Calculate and track Guarantee Availability and Performance Ratio (PR) to ensure O&M providers are meeting PPA obligations.
  • Additional responsibilities as required.

Requirements:

  • Experience 3+ years in the solar industry, specifically within O&M, Performance Engineering, or Asset Management.
  • Solar Expertise: Understanding of DC/AC ratios, clipping losses, inverter operating curves, and the impact of soiling/shading.
  • Education: B.S. in Electrical Engineering, Renewable Energy, or a related quantitative field.
  • Technical Skills: * Proficiency in Python (Pandas, NumPy, Scikit-learn) or R for data analysis.
  • Strong SQL skills for querying large historical datasets.
  • Hands-on experience with PVsyst and meteorological data (MET) stations.
  • Strong organizational skills with the ability to track & execute large volumes of ongoing compliance obligations