Business Intelligence Analyst I

About the role

The role converts raw grid data into reliable insights for power market decisions. It establishes semantic models and dashboards to support business stakeholders. The position suits a junior-to-mid level professional aiming to grow toward analytics engineering.

Analysts turn data into clear answers. They pull numbers, clean data, build dashboards, and explain what changed and why. The work supports decisions across sales, product, marketing, and operations. Strong analysts pair technical skill with business curiosity. Analysts are the bridge between data and decisions. Most analysts own recurring reports and are expected to improve them over time.

Key facts

What you'll do

Enterprise data warehouse semantic views are built and maintained in Snowflake to enable easy querying and understanding. Data quality issues are detected and resolved through validation and error analysis so datasets remain reliable. Clear documentation of data definitions and logic is created to make datasets self-serve friendly for users.

Dashboards and reports are designed and built in Sigma to satisfy business needs. Business questions that are initially vague are translated into clear, structured analyses for decision makers. Requirements are defined and refined together with business stakeholders to ensure deliverables meet expectations. Findings are presented in a way that is clear for both technical and non-technical audiences.

Code reviews are actively participated in, and feedback is incorporated to elevate data and dashboard quality. A learning-oriented team environment is shaped and supported through ongoing contributions.

Requirements

1-3 years of experience in data analysis, BI, or a related analytics role is required. A Bachelor's degree in a quantitative field or equivalent experience is necessary. Solid SQL skills, ideally with Snowflake or a similar cloud data warehouse, are required. Experience building dashboards or reports in a modern BI tool, with Sigma as a plus, is required. Comfort with large datasets and translating business logic into queries is necessary. Strong analytical thinking and attention to detail are required. The ability to balance speed and rigor in a fast-paced environment is required. Comfort with asking questions and exploring ambiguity is required rather than waiting for perfect requirements. A collaborative mindset suited to a fast-paced team is required. The ability to explain technical concepts to non-technical stakeholders is required. Self-direction in managing priorities with support from senior team members is required.

Nice to have

Familiarity with version control using Git is a plus. Exposure to dbt, Dagster, or similar data pipeline/transformation tools is a plus. Interest in Python for data analysis is a plus.

Practical notes

This is a hybrid role with 2 days in the office. The position reports to the Director of Data Management & Analytics. Yes Energy is an equal opportunity employer. Typical interview steps

Analyst interviews often include a SQL or spreadsheet exercise, a case question, and behavioral rounds. Candidates may be asked to analyze a dataset, define a metric, or estimate an outcome. Presenting findings clearly is tested as often as the analysis itself. Interviewers often test speed and clarity with a timed exercise. Explaining what the numbers mean, not just what they are, is the differentiator.

Good to know

The role focuses on turning complex power grid data into actionable insights. Snowflake and Sigma are central tools for data modeling and visualization. The position emphasizes clear communication for both technical and business audiences. Professional development is supported continuously through formal and informal learning. The team operates with a flat hierarchy and a focus on innovation and high standards.