Analytics Engineer II

Summit Utilities, Inc. is hiring an Analytics Engineer II (hybrid) in Fort Smith, Arkansas to build governed analytics data products in dbt.

Responsibilities

• Design, develop, test, and maintain dbt models that transform source data into analytics-ready datasets across one or more subject areas.
• Build and maintain dbt schema tests including not_null, unique, accepted_values, and relationships.
• Implement and run source freshness checks to enforce data quality SLAs.
• Optimize SQL transformations for performance, cost-efficiency (CU usage), and maintainability in Microsoft Fabric and Azure SQL.
• Investigate root causes of data discrepancies across upstream and downstream systems; partner with Data Engineers to remediate pipeline issues.
• Collect and document data requirements from Data Analysts, business partners, and regulatory teams, translating them into dbt model designs.
• Maintain dbt project structure including refs, sources, YAML configs, and packages such as dbt_utils and dbt_expectations, including incremental materializations.
• Create business-friendly documentation in dbt’s documentation site (model purpose, column definitions, lineage notes).
• Partner with Data Engineers on pipeline requirements and collaborate on shared standards for ingestion, modeling, and monitoring.
• Contribute to source control and CI/CD 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 via pair programming, code review, and knowledge sharing.
• Participate in standups, sprint planning, code reviews, and architecture discussions.
• Develop working knowledge of utility data domains including billing, AMI, SCADA, SAP, and GIS and the data quality needs of each operational system.

Requirements

• Bachelor’s degree in data Analytics, Information Systems, Computer Science, Mathematics, or a related field (preferred); equivalent combination of education and relevant experience will be considered.
• 3–6 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: query writing, optimization, and stored procedure understanding.
• Experience working in cloud data environments: Microsoft Fabric, Azure SQL, AWS, or similar.
• Familiarity with source control and CI/CD workflows for analytics or data projects.
• Master’s degree in a quantitative field (preferred).

Technologies

• dbt, Microsoft Fabric, Azure SQL, SQL
• dbt_utils, dbt_expectations
• Git, Azure DevOps, GitHub, Azure DevOps pipelines and GitHub Actions
• API integrations, CSV, JSON, XML
• SAP

Benefits

• Competitive pay
• Medical/dental/vision and other benefits providing flexibility, choice, and support

Knowledge, Skills, and Abilities

• Proficient SQL for querying, transformation, and analysis, including complex joins, CTEs, window functions, and subqueries.
• Working knowledge of dbt: 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.
• Working knowledge of cloud data platforms, with hands-on experience in Microsoft Fabric or Azure SQL preferred.
• Familiarity with API integrations, flat file ingestion (CSV, JSON, XML), and SAP data structures.
• Ability to work independently and own portions of delivery from requirements through deployment.
• Strong written documentation habits and ability to communicate technical decisions to teammates and stakeholders.
• Proficiency with source control tools (Git, Azure DevOps, GitHub) and collaborative development practices.
• Working knowledge of natural gas distribution and utility data systems (billing, AMI, SCADA) and understanding of data quality needs across operational systems.
• Friendly, solution-oriented team player aligned with Summit’s PEAKS values.

Position Summary

• Design, develop, test, and maintain enterprise-grade analytics data products that power reporting, regulatory submissions, and operational decision-making.
• Work independently on dbt model development within Microsoft Fabric and Azure SQL, owning specific subject areas end-to-end from source profiling through deployment and monitoring.
• Deliver trustworthy, well-modeled, and well-tested datasets that connect raw source data to business analytics.