Renewable energy analytics
Insight Builder and anomaly dashboards for wind and solar asset technicians
Collaborated with data science to build Insight Builder and specialized dashboards that help technicians act on wind and solar asset analysis.
Context
At Narrativewave, I worked as a full-stack software engineer alongside the data science team on tools for energy asset technicians.
Problem
Technicians needed a practical way to provide feedback on data analysis of wind turbines and solar panels, and to spot performance anomalies more easily.
Constraints
- Close collaboration with data science required.
- Tools needed to support real technician workflows in the field or operations context.
- Knowledge sharing had to reduce troubleshooting friction over time.
Role
Full Stack Engineer
Key responsibilities
- Joined as the first full-stack developer and partnered closely with data science.
- Built Insight Builder so technicians could provide feedback based on asset data analysis.
- Developed specialized dashboards for performance anomaly detection.
- Supported knowledge sharing aimed at reducing troubleshooting time and preventing future failures.
Technical decisions
- Product features shaped jointly with data science outputs.
- Dashboard surfaces focused on anomaly visibility and operational feedback loops.
Architecture
Full-stack product surfaces connecting data-science analysis of wind and solar assets to technician feedback and operational dashboards.
Technologies
Outcome
Shipped Insight Builder and anomaly-focused dashboards that helped technicians share knowledge and respond to asset performance signals.
Lessons learned
- Data products succeed when domain experts can contribute feedback into the system.
- Anomaly visibility is only useful when paired with operational knowledge-sharing loops.
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