Analytics Engineer II

Summit Utilities, Inc. is hiring a hybrid Analytics Engineer II (SGL17) in Denver, CO to build and sustain enterprise analytics data products. The role designs analytics-ready datasets in dbt and SQL across Microsoft Fabric and Azure SQL, delivering governed outputs for reporting, regulatory submissions, and operational decision-making.

Role Overview

This position owns analytics subject areas end-to-end, starting with source profiling and continuing through deployment, monitoring, and ongoing data quality. The focus is on producing trustworthy, well-modeled datasets that connect raw source data to business analytics use cases.

Responsibilities

• Design, build, and maintain dbt models that transform source data into governed analytics-ready datasets across one or more subject areas.
• Develop and maintain dbt schema tests including not_null, unique, accepted_values, and relationships, along with source freshness checks to support data quality SLAs.
• Optimize SQL transformations for performance, cost-efficiency (CU usage), and maintainability within Microsoft Fabric and Azure SQL.
• Investigate root causes of data discrepancies across upstream and downstream systems and partner with Data Engineers on remediation.
• Collect and document data requirements from Data Analysts, business partners, and regulatory teams, translating them into dbt model designs.
• Implement and maintain dbt project structure, including refs, sources, YAML configs, and packages such as dbt_utils and dbt_expectations, including incremental materializations.
• Author business-friendly documentation in dbt’s documentation site, covering model purpose, column definitions, and lineage notes.
• Collaborate with Data Engineers on shared standards for ingestion, modeling, and monitoring.
• Contribute to source control and CI/CD workflows for dbt projects, including pull request review and deployment automation.
• Support testing and validation for pipeline enhancements, schema changes, and source onboarding.
• Mentor Analytics Engineer I peers through pair-programming, code review, and knowledge sharing.
• Participate in team standups, sprint planning, code reviews, and architecture discussions.
• Build working knowledge of utility data domains including billing, AMI, SCADA, SAP, and GIS, along with corresponding data quality needs.

Required Qualifications

• 3 to 6 years of experience in analytics engineering, data engineering, data analysis, or BI development.
• Hands-on experience building and maintaining dbt models in a production or near-production environment.
• Strong relational database experience, including query writing, optimization, and understanding of stored procedures.
• Demonstrated experience working in cloud-based data environments such as Microsoft Fabric, Azure SQL, or AWS.
• Familiarity with source control practices and CI/CD workflows for analytics or data projects.
• Proficient SQL for querying, transformation, and analysis, including complex joins, CTEs, window functions, and subqueries.
• Working knowledge of dbt, including model development, schema tests, packages, and understanding of refs and sources.
• Solid understanding of ETL/ELT concepts and the data lifecycle from ingestion through consumption.
• Familiarity with data governance and metadata management practices.
• Ability to gather requirements, document assumptions, and translate analytical needs into dbt model designs.
• Skilled at root cause analysis and triage across upstream and downstream systems.
• Ability to work independently and own parts of project delivery from requirements through deployment.
• Strong written documentation habits and ability to communicate technical decisions.
• Proficiency with source control tools such as Git, Azure DevOps, and GitHub, with collaborative development practices.
• Working knowledge of natural gas distribution and utility data systems such as billing, AMI, and SCADA, including data quality needs across operational systems.
• Friendly, solution-oriented team player aligned with Summit’s PEAKS values.

Preferred Education

• Bachelor’s degree in data Analytics, Information Systems, Computer Science, Mathematics, or a related field.
• Master’s degree in a quantitative field.
• Equivalent combination of education and relevant experience will be considered.

Technologies

• dbt, Microsoft Fabric, Azure SQL, SQL
• dbt_utils, dbt_expectations
• Git, Azure DevOps, GitHub
• CI/CD
• API integrations; flat file ingestion (CSV, JSON, XML)
• SAP
• YAML
• CTEs, window functions, stored procedures

Compensation and Location

• Location: Denver, CO (hybrid)
• Salary: USD 90,000 to 111,000 per year (based on experience)

Benefits

• Competitive pay
• Medical/dental/vision
• Other benefits that provide flexibility, choice, and support to employees when they need it most