Analytics Engineer 3

The Analytics Engineer 3 is a specialized mid level technical professional who exercises independent judgment to architect, engineer, and govern the enterprise “Semantic Layer.” Unlike a report builder, this role acts as a “Logic Architect,” designing the reusable data models, security frameworks, and metric definitions that serve as the Single Source of Truth for the organization., This position is a key independent contributor and member of the System Data & Analytics team in Digital. The Analytics Engineer 3 is responsible for the full lifecycle engineering of the department’s semantic infrastructure. This role requires the exercise of discretion to determine the appropriate modeling strategy-choosing between Import, DirectQuery, or Direct Lake modes-to balance performance with data freshness. The ideal candidate moves fluidly between managing legacy SSAS partitions and architecting modern Microsoft Fabric semantic models using engineering tools like Tabular Editor and ALM Toolkit. This role operates with minimal oversight, defining the governance and security logic for their domain.

Equivalent experience will be accepted in lieu of the required degree or diploma

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field

CERTIFICATION & LICENSURE:

• Epic Cogito Certification within one year of start date.
• Microsoft Certified: Fabric Analytics Engineer Associate (DP-600) within one year of start date.

TYPICAL EXPERIENCE:

• 6 years of progressive experience in analytics engineering, business intelligence architecture, or semantic modeling.
• Experience independently architecting enterprise-grade data models.
• Experience managing the application lifecycle management of tabular models.

SKILLS AND KNOWLEDGE:

• Strong proficiency in Advanced DAX and SQL.
• Languages: Expert SQL; Advanced DAX.
• Tools: Deep proficiency in Tabular Editor (2 or 3), DAX Studio, ALM Toolkit, and Power BI Service.
• Architecture: Expert knowledge of Dimensional Modeling (Star Schema) and Composite Models.
• Engineering: Experience with CI/CD pipelines for semantic models and Git integration.
• Concepts: Deep understanding of the VertiPaq engine (compression, encoding, materialization).