Analytics Engineer II

Analytics Engineer II designs and delivers enterprise analytics data products for reporting, regulatory submissions, and operational decision-making.

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, plus source freshness checks to enforce 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 between upstream and downstream systems and partner with Data Engineers on pipeline remediation
• Collect and document data requirements from Data Analysts, business partners, and regulatory teams; translate needs into dbt model designs
• Implement and maintain dbt project structure using refs, sources, YAML configs, and packages including dbt_utils and dbt_expectations
• Configure and support incremental materializations within dbt projects
• Author clear, business-friendly documentation in dbt’s documentation site, 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 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 and the data quality needs for each system

Requirements

• Bachelor’s degree in data Analytics, Information Systems, Computer Science, Mathematics, or related field (preferred); equivalent education and relevant experience 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 understanding of stored procedures
• Demonstrated experience with 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
• Master’s degree in a quantitative field (preferred)

Tools & Technologies

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

Benefits

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

Position Summary

• Design, develop, test, and maintain enterprise-grade analytics data products that support 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, well-tested datasets bridging raw source data and business analytics
• Ideal background includes 3–6 years experience, SQL and dbt proficiency, familiarity with data governance and metadata management, and ability to translate analytical requirements into durable, well-documented data products

Location: Fort Smith, AR (hybrid)