Data Architect, Enterprise Data Platform

Your Opportunity as the Data Architect, Enterprise Data Platform The Data Architect is responsible for designing and maintaining enterprise data models that support analytics, reporting, and data-driven decision making. This role ensures that data structures are scalable, consistent, and aligned to business needs, while supporting efficient data consumption across the organization. The Data Architect contributes to enterprise analytics data governance and modeling standards by defining data structures, validating implementations, improving model quality and consistency, and working across data domains to ensure alignment between source data, engineered data layers, and published analytics assets. This role applies and enforces dimensional modeling best practices using star schema design, including fact and dimension tables, conformed dimensions, and standardized metrics. Data models are designed to support a unified semantic layer and enable accurate, consistent reporting across tools such as Tableau. Work Arrangements: Hybrid - onsite a minimum of 9 days a month primarily during core weeks as determined by the Company; maybe more as business need requires In this role you will: Data Modeling & Design Design, develop, and maintain dimensional data models using star schema methodology, including defining fact tables, dimension tables, grain, and relationships that support enterprise analytics and reporting. Ensure models are optimized for performance, scalability, and usability. Create and maintain conceptual, logical, and physical data models using appropriate modeling tools. Analyze and profile new data sources to understand structure, quality, relationships, and business context, informing appropriate modeling and architecture decisions. Model Quality & Standards Apply enterprise data modeling standards and best practices across all solutions. Validate data models for consistency, accuracy, and alignment with business requirements. Identify and resolve issues related to duplication, inconsistency, poor model design, or data quality concerns that impact analytics and reporting. Improve data model usability and clarity for downstream analytics and reporting. Represent the Enterprise Data Platform team in architecture review boards and design reviews, providing guidance on data modeling, semantic consistency, and analytics architecture considerations. Semantic Alignment & Analytics Support Establish and maintain a consistent semantic layer, including standardized metrics, dimensions, and business logic that support trusted analytics and reporting. Align data models with reporting requirements, certified data sources, and enterprise analytics standards. Support analytics teams by providing clear, well-structured, and consumable data models. Data Architecture & Solution Design Develop and guide data architecture decisions related to data structures and design patterns. Collaborate with Data Engineers to ensure data pipeline implementations align with the intent of approved data models, enterprise standards, and architectural best practices while meeting performance and scalability requirements. Partner with Data Owners, domain experts, engineers, and analytics teams to align data models with business processes, priorities, and enterprise standards. Recommend improvements to data design, storage, and structure. Ensure alignment across source, transformed, and published data layers. Governance & Documentation Support metadata, lineage, and documentation standards. Define and document data models, including structure, definitions