Enterprise Data Architect

HOYA Group•Lewisville, TX

About The Position

The Enterprise Data Architect (EDA) is responsible for establishing and advancing HOYA Vision Care's enterprise data architecture strategy, governance framework, and data management capabilities. This role provides architectural leadership across Data Governance, Master Data Management (MDM), Data Warehousing, Data Fabric, Data Integration, Analytics, and Information Architecture, developing target-state architectures and roadmaps that align with business objectives. The EDA partners with business leaders, architects, technical teams, vendors, and global stakeholders to drive enterprise data initiatives, ensure consistent adoption of standards, and deliver measurable business outcomes through influence and collaboration. Serving as the primary liaison between HOYA Group Digital, Global Vision Care teams, and regional organizations, the EDA ensures enterprise and regional requirements are aligned while maintaining a future-ready data ecosystem that supports analytics, machine learning, Generative AI, and Agentic AI capabilities.

Requirements

Bachelor's degree in Computer Science, Information Systems, Data Management, Engineering, or related discipline.
8+ years of experience in Data Architecture, Enterprise Architecture, Information Architecture, Data Management, or related disciplines.
Demonstrated experience developing enterprise data strategies and roadmaps.
Experience leading Data Governance, MDM, Data Warehouse, or enterprise data transformation initiatives.
Strong understanding of modern data architecture concepts including Data Warehousing, Data Lakes, Data Fabric, API-based integration, event-driven architecture, governance, and analytics platforms.
Experience facilitating architecture governance and architecture review processes.
Excellent communication, stakeholder management, and facilitation skills.
Demonstrated ability to influence organizational decisions without direct authority.
Ability to read, analyze, and interpret general business periodicals, professional journals, technical procedures, or governmental regulations.
Ability to write reports, business correspondence, and procedure manuals.
Ability to effectively present information and respond to questions from groups of managers, clients, customers, and the general public.

Nice To Haves

Experience establishing or maturing a Data Architecture practice.
Experience in manufacturing, supply chain, distribution, or global enterprise environments.
Experience enabling analytics, machine learning, Generative AI, or knowledge-driven solutions through enterprise data architecture, metadata, lineage, and governance capabilities.
Experience with Microsoft Azure data services and modern cloud data platforms.
Familiarity with LeanIX and enterprise architecture repositories.
Certifications such as CDMP, TOGAF, Microsoft Azure Data certifications, or equivalent.

Responsibilities

Define and evolve the enterprise data strategy, ensuring alignment with business objectives and enterprise architecture.
Develop multi-year roadmaps and target-state architectures across governance, MDM, data warehousing, integration, analytics, and information management.
Drive improvements in data quality, accessibility, consistency, and business value.
Enable advanced analytics, machine learning, Generative AI, Agentic AI, data products, semantic models, metadata management, and knowledge architecture.
Establish and mature the enterprise data architecture practice through standards, principles, governance processes, reference architectures, and decision frameworks.
Lead architecture reviews and promote consistent adoption of data architecture standards across the organization.
Continuously improve architecture capabilities and governance maturity.
Provide leadership for enterprise data governance programs.
Define data ownership, stewardship, quality, classification, retention, metadata, lineage, cataloging, and semantic standards.
Ensure trusted, compliant, and AI-ready data assets through governance and quality controls.
Advocate for data as a strategic enterprise asset.
Define enterprise information architecture, business data domains, and MDM strategy.
Establish authoritative data sources, ownership models, and master data processes.
Standardize business definitions, terminology, semantic models, and knowledge structures to support analytics, automation, and AI.
Assess current-state data environments and define future-state architectures.
Lead data warehouse modernization and Data Fabric initiatives.
Simplify the data landscape, improve interoperability, and evaluate emerging technologies.
Define architecture for data products, Data Mesh principles, AI workloads, data observability, reliability, metadata, and knowledge management.
Provide strategic architecture guidance to solution teams, engineers, architects, and vendors.
Establish reusable integration, data exchange, quality, and information management patterns.
Ensure AI, analytics, and machine learning solutions align with security, governance, interoperability, and responsible data use standards.
Lead enterprise data initiatives through governance, collaboration, and influence.
Build strong relationships with business leaders, data owners, technical teams, vendors, and global stakeholders.
Manage risks, dependencies, architectural decisions, milestones, and executive communications.
Facilitate workshops, governance forums, and architecture reviews to drive alignment and execution.
Partner with HOYA Group Digital and regional teams to align data architecture standards, governance, and roadmaps.
Translate enterprise standards into regional implementations while addressing local business needs.
Promote best practice sharing, cross-regional collaboration, and support global transformation initiatives.
Act as a two-way liaison between HOYA Group Digital, Global Vision Care teams, and regional organizations, ensuring regional insights and requirements actively influence future standards and architectural direction.
Ensure data architectures comply with industry regulations, governance requirements, and sustainability objectives.
Design energy-efficient, resource-optimized data platforms in collaboration with infrastructure teams.
Monitor emerging technologies and support sustainability reporting and compliance efforts.