Business Intelligence Analyst

About the role

GridPoint is a technology leader focused on accelerating the transition to a sustainable future through intelligent energy networks. Founded in 2003, GridPoint's platform manages energy, operational, and resiliency benefits across thousands of buildings, serving Fortune 500 enterprises, utilities, government organizations, and small businesses. The company has saved customers over $440M in energy costs and reduced over 5.7B kWh of energy usage.

Responsibilities

• Design and build customer-facing and internal dashboards in Sigma & Quick Suite, translating complex datasets into clear, actionable visualizations.
• Pull department performance metrics from Salesforce & Amazon Connect to enable near real-time monitoring of team performance/KPIs for department leads.
• Integrate and cross-reference product performance data from the GridPoint platform with Salesforce data to create unified views for customer-facing dashboards and internal executive reporting.
• Apply data science techniques to identify patterns in product and customer data, providing forward-looking insights for internal teams.
• Partner with Customer Success, Customer Support & Service, Product, Delivery, and Sales to understand reporting needs and develop well-structured, scalable dashboard solutions.
• Conduct ad-hoc analyses to support strategic business decisions and identify opportunities for improved data collection and utilization across the organization.
• Maintain and update data governance best practices, performing regular data quality checks to ensure data integrity.

Qualifications

• 2-4 years of experience in data analytics, business intelligence, or a related analytical role.
• Hands-on experience with BI/visualization platforms such as Tableau, Quick Suite, Looker, and Sigma.
• Proficiency in SQL for data querying, joining, and preparation across multiple data sources.
• Excellent written and verbal communication skills, able to present data findings to non-technical stakeholders clearly and compellingly.
• Familiarity with foundational data science concepts including statistical analysis, trend forecasting, and predictive modeling.
• Strong organizational and time-management skills.