Data Analyst (Energy)

Job Description

About the Role

This role offers an opportunity to contribute to a leading utility scale IPP within Australia’s energy transition. You will work hands‑on with operational and SCADA data across wind, solar, battery and other generation technologies, helping to identify underperformance, quantify losses, and strengthen in‑house analytics capability.

The role combines core operational analytics, performance reporting, stakeholder engagement, and continuous improvement, with scope to contribute to advanced analytics, automation and AI‑enabled tooling over time.

Key Responsibilities

• Analyse, validate, and manage SCADA and operational data across the asset portfolio, ensuring data quality and integrity.
• Build, own, and maintain data pipelines, databases, dashboards, and analytical models to support asset performance monitoring and decision‑making.
• Calculate, validate, and report asset availability, performance, curtailment, and loss metrics in line with contractual, regulatory, and internal standards.
• Analyse site‑ and component‑level performance to identify underperformance, degradation, and emerging faults, and support root cause analysis with Asset Management, O&M, and Engineering teams.
• Validate contractor‑submitted performance reports, availability calculations, and liquidated damages, and support due diligence, refinancing, and acquisition processes through performance analysis.
• Support market and operational insights through collaboration with Trading, including NEM dispatch and curtailment analysis, while championing improved analytics tools and data‑driven approaches.

About You

• Tertiary qualifications in Data Science, Engineering, Renewable Energy, Mathematics, Computer Science, Physics, or a related analytical discipline
• 3+ years’ experience in a data analytics role, within renewable energy.
• Strong proficiency in Power BI and Excel for analysis and reporting
• Working knowledge of Python or R for data analysis and automation, SQL for data querying, and experience with time‑series or SCADA data
• Interest or exposure to AI and machine learning techniques such as anomaly detection, forecasting, or classification
• Self‑motivated, organised, and capable of managing multiple priorities in a fast‑paced operational environment

If you're interested in this role, please apply or send your CV to karina.wright@enemixgroup.com