Lead Performance Engineer

Pine Gate Renewables is seeking a highly motivated Lead Performance Engineer with experience in solar operations for an opportunity to work on an evolving team charged with the optimization of 3GW+ of utility scale solar and storage assets. The lead performance engineer sits within the technical asset management team reporting into the VP of Fleet Performance and Operations. The candidate will share duties with the performance engineering team while working hand in hand with stakeholders to develop our data management infrastructure and performance optimization initiatives for asset management. This role will be central to a continuous effort toward further automating performance monitoring, reporting and diagnostics with a focus on actionable analytics.

What You'll Do:

Data & Analytics:

• Develop and maintain automated data pipelines from various sources, with a focus on reliability and scalability, to monitor asset performance and investigate underperformance across utility-scale solar and storage projects.
• Develop and implement data cleansing methodologies to ensure accurate and reliable performance data.
• Own the quality and structure of performance datasets through ETL, data validation, and statistical control processes leveraging tools to include python and azure cloud.
• Automate calculations for energy losses, performance KPIs (to include productivity, issue recurrence rates, response and RTS metrics), and investment opportunities. Champion this information with a focus on implementation for go-forward operations.
• Create dashboards, APIs, and tools to visualize and communicate priority opportunities with internal and external teams using Flask, Dash, and PowerBI, or other similar tools.
• Act as a subject matter expert and provide guidance on performance optimization, analytics, and data science-related matters.
• Develop and upskill the broader engineering team to leverage additional tooling and resources and expand team capabilities.

Operations:

• Support the reporting, and coordination, of work done to optimize the performance of the operating fleet including root cause analysis of production losses, failure quantification, and development of business cases for fleet investments.
• Develop and own energy models or digital twins for the operational fleet across the asset lifecycle, especially the transition into operations.
• Maintain a deep understanding of fleet configurations, common component failures, and external dependencies necessary to troubleshoot and triage fleet issues.
• Collaborate with internal stakeholders to identify opportunities for automation to assist in performance optimization.
• Collaborate with external stakeholders (Operations and Maintenance, various equipment OEMs, and software providers) to ensure optimal service and tools are available to the operating fleet.

Quality:

• Facilitate and champion strong working relationships with asset managers, engineers, operators, technicians and other cross-functional teams to drive data-driven decision making.
• Maintain a feedback loop to development and pre-construction project development to ensure future success of the operating fleet.
• Assist in training, documentation, and change adoption across the operating team.
• Embrace a continuous improvement mindset in an ever-changing working environment.

Must-Haves:

• Proficiency in programming utilizing python
• Proficiency in data analysis, statistical modeling, and data visualization for end users of various levels
• Strong analytical mindset with the ability to organize and interpret large operational datasets
• Familiarity with cloud-based data infrastructure (Azure preferred) including storage, compute, and orchestration. Experience with SQL and NoSQL databases
• Proficiency with data visualization (and communication to all levels) with tools such as PowerBI, Dash, Bokeh, or Flask
• Familiarity with RESTful API design, microservices architecture and asynchronous programming patterns
• Experience with version control systems such as Git and cloud development pipelines and CI/CD pipelines

Education & Certifications:

• BA/BS in engineering, data science, or computer science preferred

Work Environment:

• Remote Environment
• Up to 10%