The Role
Voltus is hiring a Residential Data Analyst Intern to help our Partnerships team make sense of the sprawling, multi-source data behind our residential virtual power plant programs. You love a good join and you know how to join five disconnected sources into one trustworthy dashboard. You're comfortable in SQL and Python, but more importantly, you're the kind of person who, when handed a CSV from one portal and an API response from another, immediately starts mapping how they relate.
Responsibilities
As a Residential VPP Data Analyst Intern, you will:
- Consolidate and link data across partner APIs, internal databases, and partner-facing portals to build a coherent picture of program performance
- Build and maintain dashboards (in Redash or similar) covering registration numbers, enrollment funnel analyses, and other key program metrics
- Manually collect interval usage data from after demand response events, and help develop processes to make this collection faster and more reliable over time
- Identify gaps, inconsistencies, and opportunities for automation in our residential data pipelines, and flag them so we can fix them
Qualifications
- Currently pursuing a degree in a quantitative or technical field (data science, statistics, computer science, engineering, economics, or similar)
- Proficiency with SQL — comfortable writing joins
- Working knowledge of Python for data analysis (pandas, basic API calls, light scripting)
- Strong instinct for how to link datasets together — you can look at two sources and quickly identify the keys, the gaps, and the gotchas
- Relentless attention to detail. When numbers don't tie out, you want to know why
- Self-starter who takes ownership beyond your immediate scope; when you see a problem, you drive it to resolution rather than assuming someone else will
- Intellectual curiosity about energy markets, distributed energy resources, or the residential clean-energy space is a strong plus
- Gritty and collaborative — kind in your interactions, focused on winning as a team