Senior Analytics Engineer

EnergyHub

15h•$130,000 - $170,000

About The Position

EnergyHub’s EV team is hiring an analytics professional to turn telematics and charging data from a large, expanding fleet of electric vehicles into insights about driver behavior, program performance, data quality, and product opportunities. The work will inform how utilities, automakers, and EnergyHub understand EV load and will help shape future products and programs. The role works with data from integrations with automakers and charger manufacturers and partners across engineering, data science, product management, client success, and OEM partnerships. The position involves analyzing large-scale EV data, improving the quality and usability of third-party data feeds, tracking fleet and charging trends, and identifying opportunities for new products and program designs. It also builds and maintains data models, dashboards, and automated reporting, while creating documentation and training materials so others can use the resulting data assets and insights. The ideal candidate is passionate about analytics, curious about EV use, and motivated to contribute to a carbon-free distributed energy future.

Requirements

At least 3 years of experience as a data analyst.
Passion for finding valuable insights in large, complex datasets and curiosity about electric vehicles and how people use them.
Ability to creatively infer or generate needed data from available information and clearly articulate the limitations of that inference.
Experience developing useful and visually compelling analytics dashboards.
Experience developing automated reporting systems with business intelligence tools.
Experience assessing and improving data quality, with comfort working with messy, high-volume time-series data from third-party sources.
Ability to translate analytical findings into product or business recommendations and communicate them clearly to technical and non-technical audiences.
Strong communication skills and ability to develop relationships with colleagues, clients, and external partners.
Ability to describe an ideal analytics schema to data engineering colleagues and work with them to improve a data warehouse.
Experience with one or more BI tools, cloud data warehouses, data transformation frameworks, and data science tools; examples include Tableau, Sigma, Looker, Snowflake, Redshift, BigQuery, dbt, Python/Jupyter, Julia, and R.
Experience with data warehouse architecture.
Commitment to a carbon-free distributed energy future and to empowering users through timely, accurate, actionable data.

Nice To Haves

Extensive experience with dbt, Snowflake, and SQL.
Experience with EV, telematics, connected-vehicle, charging, or other IoT device data, or with the energy or utility industry.
Experience working with third-party API data and partner-delivered data feeds, including defining data contracts and quality standards.
Strong background in mathematics and statistics to support clients in understanding complex statistics and collaborate with data scientists using the analytics platform for statistical analysis.
Experience supporting product discovery or go-to-market decisions with quantitative analysis.

Responsibilities

Analyze large-scale EV telematics and charging data from multiple OEM and charger integrations to identify insights into driver charging behavior, program enrollment and retention, event participation, and load-shifting outcomes.
Define, monitor, and improve data quality for EV OEM data feeds by identifying gaps, latency, duplicates, and anomalies; building automated checks; and working with engineering and OEM partners to address root causes.
Track and report trends across the EV fleet, including vehicle and charger mix, charging patterns by time of day and season, home versus public charging, and behavioral changes as programs and incentives change.
Build documentation and training materials that enable others to use created data assets and insights independently.
Identify and quantify opportunities for new EV products and program designs, and partner with product managers to validate opportunities using data.
Build and maintain data models, dashboards, and automated reporting in EnergyHub’s BI stack for product, client success, and utility clients.
Collaborate with engineering, data science, product management, client success, and OEM partnership teams to develop business logic, detailed requirements, and research questions.
Perform other duties as assigned.