Enterprise Data Architect 5462

We are seeking an experienced Enterprise Data Architect to lead the design and implementation of a modern enterprise data architecture that enables advanced analytics, AI, and data-driven decision making across the organization.

This is a hands-on technical leadership role focused on creating scalable, governed, and business-aligned data solutions. The ideal candidate will establish enterprise data standards, drive cross-functional alignment, and build the architectural foundation necessary to support business intelligence, artificial intelligence, and operational excellence initiatives.

The Enterprise Data Architect will work closely with technology teams, business stakeholders, data governance leaders, and executive leadership to create a unified and trusted enterprise data ecosystem.

• Assess and evaluate the current enterprise data landscape, including data platforms, integration technologies, analytics environments, APIs, and operational systems.
• Define and maintain the target-state enterprise data architecture and roadmap.
• Establish data architecture standards, patterns, and best practices across multiple business domains.
• Develop enterprise-wide data models, naming conventions, and semantic consistency standards.
• Ensure data architecture aligns with organizational goals, future growth, and digital transformation initiatives.

• Design scalable architectures that support analytics, reporting, machine learning, and AI capabilities.
• Define integration approaches for connecting data across enterprise platforms and business functions.
• Establish architectural guidance for data warehouses, data lakes, semantic layers, APIs, and data virtualization technologies.
• Evaluate emerging technologies and recommend solutions that align with enterprise architecture objectives.

• Define frameworks for data governance, stewardship, ownership, and accountability.
• Establish standards for data quality, lineage, metadata management, and lifecycle management.
• Ensure enterprise data architecture incorporates security, privacy, compliance, and regulatory requirements.
• Collaborate with security, legal, compliance, and risk teams to maintain data governance standards.
• Promote enterprise-wide adoption of data management policies and controls.

• Partner with business and technology leaders to understand data needs and priorities.
• Facilitate collaboration between engineering, analytics, operations, finance, HR, supply chain, and other functional areas.
• Provide architectural oversight for strategic data initiatives and transformation programs.
• Influence stakeholders and drive adoption of enterprise standards across diverse teams.
• Mentor technical teams and provide thought leadership on enterprise data architecture practices.
• Create practical architecture artifacts, standards, and governance processes that support execution.
• Validate architectural decisions through real-world use cases and business outcomes.
• Identify opportunities to improve data accessibility, consistency, reliability, and usability across the organization.
• Stay current on industry trends, emerging technologies, and best practices in data architecture, governance, and AI enablement.

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related technical discipline. Advanced degree preferred.
• 12+ years of experience in data management, data engineering, or enterprise data architecture.
• 5+ years of experience defining enterprise-wide data standards, architecture frameworks, and integration strategies.
• Demonstrated experience designing and implementing enterprise-scale data architectures across multiple business domains.
• Strong knowledge of data modeling, master data management, metadata management, and enterprise integration patterns.
• Experience with cloud-based data platforms, analytics ecosystems, data warehouses, and data virtualization technologies.
• Understanding of semantic modeling, knowledge management, ontologies, or related architectural concepts.
• Experience establishing data governance, lineage, data quality, and stewardship frameworks.
• Familiarity with enterprise systems such as ERP, HRIS, CRM, financial, manufacturing, or operational platforms.
• Strong communication and stakeholder management skills with the ability to engage technical and non-technical audiences.
• Proven ability to influence across organizational boundaries and lead enterprise-wide initiatives.

• Experience supporting AI, machine learning, or advanced analytics initiatives.
• Knowledge of semantic layer, ontology, or knowledge graph technologies.
• Experience in highly regulated industries such as aerospace, defense, healthcare, financial services, or government contracting.
• Familiarity with data security, privacy, compliance, and regulatory frameworks.
• Experience implementing federated data…