Data Architect

Job Summary

Design, govern, and enable high-quality enterprise data model that support enterprise reporting, analytics, and AI-driven use cases leveraging the Data Vault 2.0 modeling methodology. This role bridges business requirements and technical implementation, ensuring data is structured, trusted, reusable, and aligned to enterprise architecture standards, primarily within Microsoft Fabric and the enterprise analytics ecosystem. #LI-IB2

Key Responsibilities

• Design, maintain, develop and execute conceptual, logical, and physical data models for BI and analytics. 
• Strong working knowledge of modern data and analytics architectures and hands on implementation experience 
• Define and enforce semantic modeling standards and metric definitions 
• Partner with Data Engineering to align lakehouse and warehouse architectures 
• Enable self-service and managed BI through reusable semantic models 
• Translate business requirements into scalable data structures 
• Support Microsoft Fabric adoption and analytics architecture patterns 
• Establish data modeling patterns, naming standards, and guidelines 
• Contribute to data governance, quality, lineage, and metadata initiatives 
• Support AI and advanced analytics readiness 

Scope & Impact 

• Improves data trust, consistency, and usability for decision-making 
• Influences analytics design across all enterprise domains 
• Reduces duplication and inconsistencies across reports and data products 
• Supports enterprise analytics modernization initiatives 

Key Relationships 

• Business stakeholders and product owners 
• Data Engineering and BI teams 
• Governance, security, and platform teams 
• Analytics consumers 

Management Responsibilities

Preferred Qualifications

• Demonstrated 5+ years of experience designing and maintaining enterprise‑scale conceptual, logical, and physical data models that support reporting, analytics, and AI use cases.  
• Strong expertise in dimensional and analytical data modeling, including defining canonical business entities, shared metrics, and reusable semantic layers.  
• Proven ability to translate business requirements into scalable, governed data structures, balancing flexibility, performance, and long‑term maintainability.  
• Solid understanding of modern analytics architectures, including lakehouse, warehouse, and medallion patterns, and how data models align to each layer.  
• Working knowledge of data governance, data quality, lineage, and metadata practices, and how these are embedded into model design rather than retrofitted 

Preferred Skills 

• Experience modeling data in Microsoft Fabric, including alignment with OneLake, Lakehouse/Warehouse, and Power BI semantic models. [ 
• Hands‑on experience with Data Vault 2.0 as an integration and history‑preserving modeling approach, paired with dimensional models for analytics consumption. Word] 
• Experience defining and enforcing enterprise data modeling standards, naming conventions, and design guidelines across multiple domains.  
• Familiarity with AI‑ and ML‑ready data design, ensuring data models can support feature reuse, advanced analytics, and future AI workloads. [ 
• Experience working in a governed self‑service analytics environment, enabling reuse while maintaining consistency and trust 

Minimum Qualifications

All applicants must be able to complete pre-employment onboarding requirements (if selected) which may include any/all of the following: criminal/civil background check, drug screen, and motor vehicle records search, in compliance with any applicable laws and regulations.

Certifications

Work Environment/Physical Demands

Competencies

Salary Plan

Job Grade