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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Enteprise Data Architect - **Company:** Propertyvalue Ashley Furniture Industries - **Location:** Tampa, FL, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Data Architecture, Data Definition Language, Data Governance, Data Sharing, Data Structures, Logical Data Models, Meta-Data Management, Metadata Repositories, Reference Data, Search Technologies, Enterprise Data Management, Togaf, Data Layers, Data Management, Domain Driven Design, Data Inconsistencies - **Published:** August 21, 2026 - **Apply:** https://www.dice.com/job-detail/9881425c-eae8-4f3f-8c57-02ae62216e72 ## About the Role * 5+ years of experience in enterprise data modeling, data architecture, information architecture, semantic modeling, or a closely related discipline. * Demonstrated experience developing conceptual and logical data models across multiple business domains. * Strong ability to translate business language into precise definitions, entities, relationships, and reusable data structures. * Experience facilitating cross-functional alignment with business SMEs, data architects, analysts, engineers, product managers, and governance stakeholders. * Familiarity with metadata management, data catalogs, data governance, data products, and data quality concepts. * Strong written communication skills, including the ability to produce clear model documentation and decision records., * Experience with enterprise modeling tools, metadata repositories, catalog platforms, or knowledge graph / ontology patterns. * Experience with domain-driven design, master data, reference data, canonical models, semantic layers, or data contracts. * Familiarity with AI grounding, RAG, vector search, or ontology integration patterns. * CDMP, DAMA, TOGAF, or comparable data architecture / data management certification. Success Measures * Adoption of enterprise models and definitions across teams * Reduced time spent resolving data inconsistencies * Improved speed and quality of data product and analytics delivery * Increased confidence in data used for business decisions and AI ## Description * The Enterprise Data Architect defines and enables the shared data foundation that ensures consistent understanding of core business entities across the enterprise. * This role translates business concepts into reusable enterprise models, authoritative definitions, and contextual frameworks that accelerate decision-making, improve data product delivery, and ensure AI and analytics solutions operate on trusted, aligned data. * By establishing a common language for data, this role reduces ambiguity, strengthens cross-domain alignment, and enables teams to deliver faster with confidence. What success looks like * Business-critical data is consistently defined and understood across teams * Data products, analytics, and AI solutions are built on trusted, aligned definitions * Cross-domain data conflicts are resolved quickly with clear decisions * Teams spend less time reconciling data and more time delivering business value * Enterprise data context is discoverable, reusable, and embedded in delivery workflows What you'll do Enterprise Data Architecture & Modeling * Define and evolve enterprise conceptual and logical data models for key business domains * Establish clear representations of business entities, relationships, and domain boundaries * Provide architectural guidance that promotes consistency while supporting team autonomy * Apply enterprise modeling and naming standards through practical guidance and review * Identify gaps in standards based on real-world usage and drive continuous improvement Shared Definitions & Business Alignment * Develop and maintain authoritative definitions for cross-domain business concepts * Enable a common business language that supports reporting, analytics, and AI * Identify risks where inconsistent definitions could impact business outcomes and drive stakeholder alignment to resolve those conflicts Data Product Enablement * Partner with Data Product Management and delivery teams to embed enterprise context into design * Ensure data context is usable and reliable for AI, analytics, and semantic layers * Ensure alignment between data products and enterprise models without slowing delivery * Provide guidance that improves delivery speed and reduces rework * Support the operationalization of data context in catalogs, semantic layers, and data products Key Deliverables * Enterprise models for priority domains and shared concepts * Approved definitions for key business entities and metrics * Resolution of cross-domain data definition conflicts * Architectural guidance that improves alignment across data products * Reusable, published data context for enterprise consumption Role Boundaries This role does not own physical data design, pipelines, or delivery execution. 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