Analytics Engineer

• Build and support scalable data models that translate raw data into clean, business-ready datasets
• Ensure data accuracy, documentation, observability, semantic consistency, and performance
• Develop and maintain modular dbt models, semantic layers, and BI views for business analysts and executive stakeholders
• Understand evolving business trends, business logic, and cross-functional partnerships to embed context and governance in the data layer
• Develop, document, and maintain Kimball dimensional models, semantic definitions, warehouse transformation logic, and BI datasets
• Design, build, and maintain version-controlled data models supporting self-service analytics and reporting
• Ensure data quality and pipeline accuracy through automated dbt testing, lineage tracking, performance tuning, and proactive alerting
• Improve complex business logic and fragmented queries by standardizing analyst requests into documented semantic models
• Integrate data governance, metric standardization, documentation, single-source-of-truth definitions, and secure data access
• Collaborate with data team members and stakeholders; participate in standups, planning, and retrospectives
• Troubleshoot data logic issues and modeling errors and participate in analytics support activities
• Identify improvements to data transformation processes and semantic definitions
• Contribute to the analytics platform, dbt models, semantic layers, and BI reporting frameworks
• Independently own analytics engineering workstreams and modeling roadmap items
• Develop domain expertise in business metrics and data definitions