Analytics Engineer II

Summit Utilities Inc builds enterprise-grade analytics data products that help teams deliver reliable reporting, support regulatory submissions, and improve operational decision-making. In this hybrid role based in Arkansas, you will focus on independent dbt model development within Microsoft Fabric and Azure SQL, owning subject areas end-to-end from source profiling through deployment and ongoing monitoring.

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 (for example not_null, unique, accepted_values, and relationships) and implement 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 environments.
• Investigate root causes of data discrepancies across upstream and downstream systems, partnering with Data Engineers to remediate pipeline issues.
• Collect and document data requirements from Data Analysts, business partners, and regulatory teams, then translate those needs into dbt model designs.
• Implement and maintain dbt project structure including refs, sources, YAML configurations, packages (dbt_utils, dbt_expectations), and incremental materializations.
• Author clear, business-friendly documentation in dbt documentation, including model purpose, column definitions, and lineage notes.
• Collaborate with Data Engineers on pipeline requirements and 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 new 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 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 including query writing, optimization, and understanding stored procedures.
• Demonstrated experience working within cloud-based data environments (Microsoft Fabric, Azure SQL, AWS, or similar).
• Familiarity with source control practices and CI/CD workflows for analytics or data projects.
• Proficiency in SQL for querying, transformation, and analysis, including complex joins, CTEs, window functions, and subqueries.
• Working knowledge of dbt: ability to develop models, write schema tests, use packages, and understand 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 in 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 and flat file ingestion (CSV, JSON, XML), and SAP data structures.
• Ability to work independently and own portions of project 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.
• Master’s degree in a quantitative field is preferred.

Technologies

• dbt
• Microsoft Fabric
• Azure SQL
• SQL
• Azure DevOps
• Git
• GitHub
• dbt_utils
• dbt_expectations
• YAML
• CSV
• JSON
• XML
• SAP
• ETL
• ELT

Benefits

• Competitive pay
• Medical/dental/vision and other benefits

Location and Work Setup

Fayetteville, AR (hybrid). This hybrid role may be based in one of Summit Utilities’ offices in Little Rock, Fort Smith, or Fayetteville, Arkansas.