Analytics Engineer II - dbt, SQL & Cloud Analytics (Hybrid)

Summit Utilities; Fort Smith (AR); Hybrid; USD 90,000 - 120,000; Full time

Job summary

Summit Utilities, Inc. in Arkansas is seeking an Analytics Engineer II to design, develop, test, and maintain analytics data products powering reporting, regulatory submissions, and operational decision-making.

You will work with dbt models in Microsoft Fabric and Azure SQL, own subject areas end-to-end, and collaborate with Data Engineers to ensure high-quality, well-documented data assets. The ideal candidate has 3–6 years of analytics engineering experience, strong SQL, dbt expertise, and

Qualifications

• 3–6 years of analytics engineering, data engineering, data analysis, or BI development.
• Strong experience with relational databases, including query writing, optimization, and stored procedures.
• Hands-on experience building and maintaining dbt models in production or near-production environments.

Responsibilities

• Design, build, and maintain dbt models transforming source data into analytics-ready datasets.
• Write and maintain dbt schema tests and source freshness checks to enforce data quality SLAs.
• Optimize SQL transformations for performance and cost in Fabric/Azure SQL environments.
• Collaborate with Data Engineers to remediate pipeline issues and document data requirements for models.
• Contribute to source control and CI/CD workflows for dbt projects and documentation.

Education

Bachelor's degree in data Analytics, Information Systems, Computer Science, Mathematics, or related field

Tools

dbt

Microsoft Fabric

Azure SQL

AWS

Git

Azure DevOps

Job description

Summit Utilities, Inc. in Arkansas is seeking an Analytics Engineer II to design, develop, test, and maintain analytics data products powering reporting, regulatory submissions, and operational decision-making.

You will work with dbt models in Microsoft Fabric and Azure SQL, own subject areas end-to-end, and collaborate with Data Engineers to ensure high-quality, well-documented data assets. The ideal candidate has 3–6 years of analytics engineering experience, strong SQL, dbt expertise, and