Analyst, Performance

About the role

The Performance Analyst will support building and maintaining production pipelines, analytics systems, and reporting workflows across TerraForm Power’s renewable fleet. The role will maintain pipelines for generation reporting processes, vendor API integrations and performance analytics. This role focuses on data engineering and performance analytics, ensuring high-quality, reliable data to support asset performance monitoring and operational decision-making.

Responsibilities

• Data Engineering & Pipelines
• Build, maintain, and enhance Python-based ETL pipelines on Databricks using Delta Lake architecture
• Manage end-to-end data flows, including ingestion, transformation, validation, and delivery to reporting tools
• Support vendor API integrations, including authentication, schema management, and data quality monitoring
• Implement data pipeline best practices, including error handling, logging, and automated alerting
• Performance Analytics & Reporting
• Support generation reporting processes and performance analytics across wind, solar, and storage assets
• Aid in automating production guarantee calculations, including integration of weather datasets and performance models
• Build and maintain reporting tools, dashboards, and automated outputs (e.g., Streamlit apps, HTML reports)
• Perform data validation and support ongoing data quality improvement efforts
• Data Management & Governance
• Maintain and expand data models and table schemas for assigned datasets
• Document data pipelines, data dictionaries, and system processes
• Participate in code reviews and contribute to team engineering standards
• Cross-Functional Collaboration
• Partner with internal stakeholders to support data and reporting needs
• Aid in troubleshooting data issues and supporting ad hoc analyses
• Contribute to continuous improvement of analytics tools, systems, and processes

Qualifications

• Education: Bachelor’s degree in Computer Science, Data Engineering, Engineering, or a related technical field
• Experience: 0–2 years of relevant experience (internship or academic experience acceptable)
• Technical Skills: Proficiency in Python and familiarity with SQL; Exposure to data pipelines, APIs, and structured/semi-structured datasets; Experience or familiarity with Databricks, Spark, or Delta Lake; Exposure to data visualization or reporting tools (e.g., Streamlit, Power BI, Tableau); Familiarity with time-series or renewable energy data; Exposure to SCADA or performance platforms (e.g., Bazefield)
• Core Competencies: Strong analytical and problem-solving skills; High attention to detail and commitment to data quality; Ability to learn quickly and work in a fast-paced environment; Strong communication and collaboration skills; Intellectual curiosity and ownership mindset