Sr. Analytics Engineer

Axogen•Tampa, FL

7h•$103,548 - $129,435•Onsite

About The Position

The Sr. Analytics Engineer will report to the Sr. Manager, Business Analytics and serve as the technical owner of Axogen's enterprise semantic models, KPI framework, and BI architecture supporting Commercial, Finance, Operations, and Executive reporting. This role partners with Business Analysts, Finance Business Partners, Commercial Operations, FP&A, and IT to ensure consistent metric definitions, scalable reporting, and high-quality decision support. The ideal candidate has deep expertise in dimensional modeling, DAX, semantic layer design, performance optimization, Power BI, and Microsoft Fabric best practices.

Requirements

Bachelor's degree in Information Systems, Computer Science, Business Analytics, Finance, Engineering, or a related field.
Minimum 5 years of experience in Business Intelligence, Analytics Engineering, Data Modeling, or a related role.
Advanced experience developing enterprise Power BI solutions, including semantic models, reports, dashboards, and governed datasets.
Expert-level DAX development experience and strong understanding of calculation logic, reusable measures, and KPI frameworks.
Strong understanding of dimensional modeling, data warehousing, and semantic layer design.
Strong SQL skills and working knowledge of relational database structures.
Experience working with Finance, Commercial Analytics, Sales Operations, or Business Intelligence functions.
Excellent communication, stakeholder management, documentation, and problem-solving skills.
Ability to manage multiple projects and priorities in a fast-paced environment.

Nice To Haves

Experience with Microsoft Fabric, Power BI Premium, or enterprise Power BI deployment models.
Experience with Tabular Editor, calculation groups, model scripting, or related tabular model development tools.
Experience with Azure DevOps, Git, PBIP, CI/CD, and deployment pipelines.
Experience designing enterprise semantic models and KPI governance frameworks.
Familiarity with Databricks, Azure SQL, cloud data platforms, and modern data-warehouse architectures.
Experience supporting executive reporting, FP&A, Commercial Analytics, Sales Operations, or Operations reporting.
Relevant medical device or biopharma experience a plus.

Responsibilities

Own and maintain enterprise Power BI semantic models supporting Commercial, Finance, Operations, and Executive reporting.
Design and manage model architecture including fact tables, dimensions, hierarchies, relationships, perspectives, metadata, and security.
Establish semantic model standards, naming conventions, and governance practices.
Define and document KPI calculations, business rules, and reporting definitions.
Develop and maintain advanced DAX measures, calculation groups, and reusable business logic.
Partner with business stakeholders to translate requirements into governed metric definitions.
Ensure KPI consistency across Power BI reports, dashboards, and self-service analytics.
Support complex financial, sales, territory, commission, pricing, and operational reporting requirements.
Optimize semantic models for scalability, refresh performance, query speed, and usability.
Identify opportunities to reduce model complexity, improve maintainability, and eliminate duplicate logic.
Troubleshoot performance bottlenecks and implement best practices in model design.
Support migration of BI assets to Microsoft Fabric/Databricks and enterprise semantic model architecture.
Build and enhance enterprise Power BI datasets, reports, and dashboards.
Support thin-report architecture and self-service analytics initiatives.
Collaborate with Business Analysts and Finance Business Partners on reporting solutions.
Assist in development of executive, commercial, operational, and financial reporting.
Support BI governance, change management, documentation, and release-management processes.
Manage semantic model version control, testing practices, deployment pipelines, and production release standards.
Utilize Git, Azure DevOps, PBIP, Tabular Editor, and Fabric development frameworks, as applicable.
Maintain technical documentation, model inventories, and change logs.
Implement Row-Level Security (RLS), security modeling, data governance controls, and change-management processes.