Job description

Job Summary The Senior Performance Engineer is responsible for expected-versus-actual energy performance across SunStrong’s serviced fleet, spanning residential systems, commercial and industrial sites, community solar, and utility-scale projects. This role models production, quantifies and defends contractual performance obligations, and drives underperformance to root cause with operations and field services. As the senior technical authority on fleet performance, the position sets the data requirements behind performance reporting, advises on dashboard and analytics development rather than building it, and partners with asset management and O&M on billing and settlement accuracy. The role sits on the Fleet Management Technology team and requires equal comfort with a residential inverter fleet, a metered utility-scale PPA settlement, and the data platform that carries both. Responsibilities • Model and monitor energy performance across residential, C&I, community solar, and utility-scale assets in PlantPredict and the fleet monitoring platforms (AlsoEnergy, Power Factors, 3E), comparing metered production against simulation using weather and irradiance data from Solcast, SolarAnywhere, and Open-Meteo. • Calculate and defend contractual performance metrics including availability, performance ratio, production guarantees, and liquidated damages exposure, and produce the recurring analysis that supports billing, PPA and lease invoicing, and investor and securitization reporting. • Evaluate billing and settlement accuracy with the asset management and O&M teams, reconciling metered, monitored, and invoiced quantities and resolving discrepancies at the source. • Investigate underperformance to root cause across inverters, meters, communications, energy storage, and site conditions, and drive corrective work to closure with O&M and field services. • Direct the data requirements for fleet performance — tags, granularity, units, timestamps, and quality rules — and support data collection, ingestion, and reconciliation with the data platform team. • Advise on the development of Power BI dashboards and performance reporting, defining metric definitions, calculation logic, and acceptance criteria, and validating output rather than building the reports directly. • Define monitoring, revenue-grade metering, and telemetry requirements for new and retrofitted sites, and validate commissioning data before a site is accepted into the fleet. • Establish performance baselines and data mappings for newly acquired or transitioned portfolios, including migration from legacy monitoring platforms. • Validate storage system performance against contracted operating modes, including dispatch behavior, state of health, cycling, and demand-charge and tariff-driven response. • Apply AI tooling and agentic workflows to accelerate fleet diagnostics, anomaly triage, and recurring analysis, and define where model output requires engineering verification before it is relied on. • Serve as technical reviewer for warranty, insurance, and equipment claims requiring quantified production loss, and mentor junior engineers and analysts on performance methods. Qualifications • Bachelor’s or Master’s degree in engineering, physics, or a related technical field. • 8+ years in solar or storage performance engineering, asset performance management, or renewable O&M engineering, including 3+ years supporting commercial or utility-scale assets. • Hands-on experience with PV performance modeling in PlantPredict (PVsyst or SAM acceptable as a secondary), and with satellite irradiance and weather datasets including Solcast, SolarAnywhere, and Open-Meteo. • Working experience with fleet monitoring and asset performance platforms including AlsoEnergy, Power Factors, and 3E, including data extraction, tag mapping, and alarm configuration. • Proficiency in SQL and in Python for engineering analysis (pandas, numpy, pvlib or equivalent). • Practical fluency with AI tooling — coding assistants, LLM-based analysis, and agentic workflows — applied to engineering work, with sound judgment on where output must be verified. • Demonstrated ability to specify data requirements, validation rules, and reconciliation logic for engineering and BI teams, and to review dashboards and reporting for correctness. • Working knowledge of monitoring, metering, and SCADA data acquisition, including common protocols and vendor APIs (Modbus, SunSpec, DNP3, REST). • Familiarity with leased, PPA, and securitized portfolios, including production and availability guarantees, settlement mechanics, and investor reporting obligations. • Battery energy storage experience covering BMS behavior, state-of-health analysis, and dispatch validation. • Ability to work against incomplete legacy as-built and monitoring data, and to state assumptions and uncertainty explicitly to engineering, asset management, and capital partners.

Requirements

Must-haves

Evaluate billing and settlement accuracy with the asset management and O&M teams, reconciling metered, monitored, and invoiced quantities and resolving discrepancies at the source.
Investigate underperformance to root cause across inverters, meters, communications, energy storage, and site conditions, and drive corrective work to closure with O&M and field services.
Direct the data requirements for fleet performance — tags, granularity, units, timestamps, and quality rules — and support data collection, ingestion, and reconciliation with the data platform team.
Advise on the development of Power BI dashboards and performance reporting, defining metric definitions, calculation logic, and acceptance criteria, and validating output rather than building the reports directly.
Define monitoring, revenue-grade metering, and telemetry requirements for new and retrofitted sites, and validate commissioning data before a site is accepted into the fleet.
Establish performance baselines and data mappings for newly acquired or transitioned portfolios, including migration from legacy monitoring platforms.
Validate storage system performance against contracted operating modes, including dispatch behavior, state of health, cycling, and demand-charge and tariff-driven response.
Apply AI tooling and agentic workflows to accelerate fleet diagnostics, anomaly triage, and recurring analysis, and define where model output requires engineering verification before it is relied on.
Serve as technical reviewer for warranty, insurance, and equipment claims requiring quantified production loss, and mentor junior engineers and analysts on performance methods.
Bachelor’s or Master’s degree in engineering, physics, or a related technical field.
8+ years in solar or storage performance engineering, asset performance management, or renewable O&M engineering, including 3+ years supporting commercial or utility-scale assets.
Hands-on experience with PV performance modeling in PlantPredict (PVsyst or SAM acceptable as a secondary), and with satellite irradiance and weather datasets including Solcast, SolarAnywhere, and Open-Meteo.
Working experience with fleet monitoring and asset performance platforms including AlsoEnergy, Power Factors, and 3E, including data extraction, tag mapping, and alarm configuration.
Proficiency in SQL and in Python for engineering analysis (pandas, numpy, pvlib or equivalent).
Practical fluency with AI tooling — coding assistants, LLM-based analysis, and agentic workflows — applied to engineering work, with sound judgment on where output must be verified.
Demonstrated ability to specify data requirements, validation rules, and reconciliation logic for engineering and BI teams, and to review dashboards and reporting for correctness.
Working knowledge of monitoring, metering, and SCADA data acquisition, including common protocols and vendor APIs (Modbus, SunSpec, DNP3, REST).
Familiarity with leased, PPA, and securitized portfolios, including production and availability guarantees, settlement mechanics, and investor reporting obligations.
Battery energy storage experience covering BMS behavior, state-of-health analysis, and dispatch validation.
Ability to work against incomplete legacy as-built and monitoring data, and to state assumptions and uncertainty explicitly to engineering, asset management, and capital partners.

Nice-to-haves

None flagged.

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