Solar EYA / Asset Performance & Analytics Lead

GMR Group

Delhi

On-site

INR 1,800,000 - 3,200,000

Full time

6 days ago
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Job summary

GMR Group's Renewables Engineering team seeks a Solar EYA / Asset Performance & Analytics Lead with 5–10 years of solar experience to develop bankable EYA, performance models, and analytics frameworks for utility‑scale projects.

The role ensures accurate generation forecasts and alignment between engineering assumptions and financial models, feeding asset performance back into design decisions to protect returns and long‑term value.

Qualifications

  • 5–10 years of solar engineering experience with an IPP, OEM, renewable energy developer, or technical consultant.
  • Direct experience with lender technical due diligence and IE interactions preferred.
  • Proficiency in PVsyst and solar energy yield assessments.
  • Strong understanding of PR, system losses, meteorological data, and uncertainty analysis.
  • Ability to translate engineering data into financial implications.

Responsibilities

  • Conduct Solar energy production assessments (P50, P75, P90) and uncertainty analysis.
  • Generate comprehensive pre-construction energy yield reports for internal approvals and external lenders/investors.
  • Conduct sensitivity and uncertainty analysis.
  • Define and validate loss assumptions (DC, AC, availability, degradation).
  • Plant performance modeling and analytics; track post‑COD performance.
  • Identify underperformance root causes and create standardized dashboards/reports.
  • Support lender due diligence and IE engagements.

Skills

Solar yield assessments
Performance modeling
Analytics dashboards
Lender due diligence
Data interpretation

Education

B.Tech / M.Tech in Engineering / Energy
Data analytics exposure

Tools

PVsyst
Excel
Python
Power BI

Job description

Solar EYA / Asset Performance & Analytics Lead

We are seeking an experienced and motivated Solar EYA / Asset Performance & Analytics Lead for GMR Renewables Engineering team with 5-10 Years of relevant experience responsible for developing bankable Solar Energy Yield Assessments (EYA), performance models, and analytics frameworks for utility–scale solar and hybrid projects.

The role ensures accurate generation forecasts, alignment between engineering assumptions and financial models, and continuous feedback from operating assets back into design and technology decisions, thereby protecting project returns and long‑term asset value.

ORGANISATION CHART

└─ Lead Design & Engineering (Solar & Wind)

└─ Solar EYA / Asset Performance & Analytics Lead

KEY ACCOUNTABILITIES
  • Conduct Solar energy production assessments (P50, P75, P90) and uncertainty analysis.
  • Generate comprehensive pre‑construction energy yield reports for internal approvals and external investors/lenders
  • Conduct sensitivity and uncertainty analysis
  • Define and validate loss assumptions (DC, AC, availability, degradation)
  • Plant performance modeling, and analytics
  • Track post‑COD plant performance and PR
  • Identify underperformance root causes
  • Create standardized performance dashboards and reports
  • Support lender due diligence and IE engagements
  • Advanced proficiency in PVsyst (mandatory)
  • Strong understanding of: Solar plant design and system losses, Performance Ratio (PR), availability, degradation, Meteorological data, uncertainty analysis
  • Strong understanding of FDRE, RTC, and BESS integration in renewable energy systems.
  • Ability to translate engineering data into financial implications
EXTERNAL INTERACTIONS
  • OEMs, EPC contractors, Lender & Owner’s engineer, technical consultants
INTERNAL INTERACTIONS

CBO, Project development, O&M and Asset Management teams

EDUCATION QUALIFICATIONS
  • B.Tech / M.Tech in Engineering / Energy
  • Additional exposure to data analytics or statistics preferred
RELEVANT EXPERIENCE
  • 5-10 years in Solar engineering preferably with an IPP, OEM, renewable energy developer, or technical consultant.
  • Direct experience with lender technical due diligence and IE interactions preferred
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