Analytics Engineer II

Analytics Engineer II role supporting enterprise analytics data products across reporting, regulatory submissions, and operational decision-making.

• Location: Little Rock, AR (hybrid)
• Experience: 3+ years required
• Education: Bachelor’s degree in data Analytics, Information Systems, Computer Science, Mathematics, or a related field (equivalent combination of education and relevant experience will be considered)

Responsibilities

• Design, build, and maintain dbt models that transform source data into governed, analytics-ready datasets across one or more subject areas
• Create and maintain dbt schema tests including not_null, unique, accepted_values, and relationships
• Implement source freshness checks to enforce data quality SLAs
• Optimize SQL transformations for performance, cost-efficiency (including CU usage), and maintainability within Microsoft Fabric and Azure SQL
• Investigate root causes of data discrepancies between upstream and downstream systems and partner with Data Engineers on remediation
• Gather and document data requirements from Data Analysts, business partners, and regulatory teams; translate requirements into dbt model designs
• Maintain dbt project structure, including refs, sources, YAML configs, and packages such as dbt_utils and dbt_expectations
• Use and manage incremental materializations as part of dbt model delivery
• Author clear, business-friendly documentation in dbt’s documentation site (model purpose, column definitions, lineage notes)
• Collaborate with Data Engineers on ingestion, modeling, and monitoring standards
• 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 via 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, including data quality needs across operational systems

Requirements

• 3–6 years of experience in analytics engineering, data engineering, data analysis, or BI development
• Hands-on experience building and maintaining dbt models in production or near-production environments
• Strong relational database experience: query writing, optimization, and understanding stored procedures
• Demonstrated experience in cloud data environments: Microsoft Fabric, Azure SQL, AWS, or similar
• Familiarity with source control and CI/CD workflows for analytics or data projects
• Proficiency in SQL for querying, transformation, and analysis (complex joins, CTEs, window functions, subqueries)
• Working knowledge of dbt: developing models, writing schema tests, using packages, and understanding refs and sources
• Solid understanding of ETL/ELT 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; Microsoft Fabric or Azure SQL experience preferred
• Familiarity with API integrations and flat file ingestion including CSV, JSON, and XML, plus familiarity with 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 such as Git, Azure DevOps, and GitHub, including collaborative development practices
• Working knowledge of utility data systems (billing, AMI, SCADA) and data quality needs across operational systems
• Team alignment with Summit values and a solution-oriented approach
• Master’s degree in a quantitative field preferred
• Familiarity with natural gas distribution and utility data systems (billing, AMI, SCADA)

Technologies

• dbt
• Microsoft Fabric
• Azure SQL
• Azure DevOps
• Git, GitHub
• SQL
• dbt_utils
• dbt_expectations
• CI/CD
• YAML
• CSV, JSON, XML
• SAP
• ETL, ELT
• Git-based source control

Benefits

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

Work Setting

• Hybrid role based in the Little Rock, Arkansas area
• May be based in an office in Little Rock, Fort Smith, or Fayetteville, Arkansas

Equal Opportunity

• All qualified applicants receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or protected veteran status