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Enterprise Data Architect (MDM, Data Catalog & AI Enablement):

Total Required Experience in Years: 12%2B Years

Mode of Work: Remote (Texas Residency Preferred)

The Enterprise Data Architect will lead the implementation of an enterprise-wide Master Data Management (MDM) and Data Catalog solution supporting structured and unstructured data assets. This role will establish semantic layers, metadata management, lineage, governance, and AI enablement capabilities that improve enterprise data discovery, trust, and reuse. The architect will bridge data engineering, governance, and AI initiatives while ensuring high-quality, well-documented data assets are available for analytics, machine learning, and generative AI workloads.

Key Responsibilities:

• Design and implement enterprise-wide MDM and Data Catalog solutions.

• Develop conceptual, logical, and physical enterprise data models.

• Build semantic layers supporting AI, analytics, and machine learning initiatives.

• Design metadata, taxonomy, ontology, and semantic tagging strategies.

• Reverse-engineer legacy databases and modernize enterprise data architectures.

• Create and maintain enterprise data dictionaries and metadata repositories.

• Automate metadata ingestion, scanning, and catalog synchronization.

• Implement data lineage and classification using:

  • Microsoft Purview

  • Unity Catalog

• Integrate enterprise data catalogs with:

  • BI platforms

  • ETL/ELT pipelines

  • Enterprise applications

• Develop APIs for metadata harvesting, automation, and event-driven integration.

• Apply enterprise data governance, security, and classification standards.

• Collaborate with product owners, data stewards, architects, and engineering teams.

• Facilitate enterprise data model reviews and governance meetings.

• Develop standards, templates, onboarding guides, and training materials.

• Monitor metadata quality, lineage, and governance KPIs.

• Provide project status updates, risk assessments, and dependency management.

Additional Responsibilities:

• Expand enterprise glossary, taxonomy, and ontology coverage.

• Align semantic attributes with lineage and data classification rules.

• Support AI-enabled data discovery and enterprise search capabilities.

• Promote enterprise data stewardship and governance best practices.

• Continuously improve metadata quality, consistency, and automation.

• Support business-led analytics and AI initiatives.

Required Skills:

• Minimum 12%2B years of overall IT/Data Architecture experience.

• Minimum 7 years as an Enterprise Data Architect implementing MDM and Data Catalog solutions.

• Minimum 4 years of Data Modeling and DBA experience with:

  • Oracle

  • Microsoft SQL Server

• Expertise with enterprise data catalog platforms including:

  • Microsoft Purview

  • Collibra

  • Alation

• Experience designing semantic/context layers for AI/ML solutions.

• Experience with AWS and Azure cloud data platforms.

• Strong understanding of:

  • Data Governance

  • Data Classification

  • Data Security

• Experience implementing:

  • Data Lineage

  • Data Integration

  • Metadata Management

• Experience with ETL/ELT platforms including:

  • Informatica

  • Fivetran

• Experience designing metadata APIs and automation frameworks.

• Strong knowledge of:

  • Conceptual Data Modeling

  • Logical Data Modeling

  • Physical Data Modeling

  • ER/Studio

• Excellent communication, documentation, and stakeholder management skills.

Preferred Skills:

• Experience with Vector Databases.

• Experience with Feature Stores.

• Python scripting and automation.

• Experience supporting Texas state government agencies.

• Experience with GitHub.

• Knowledge of Generative AI and enterprise AI governance.

• Experience implementing enterprise semantic search capabilities.

Qualifications:

• Proven experience designing enterprise-scale data architecture and governance solutions.

• Strong understanding of AI-ready metadata, semantic modeling, and enterprise data management.

• Experience leading cross-functional architecture and governance initiatives.

• Excellent analytical, problem-solving, and communication skills.

• Ability to manage multiple enterprise priorities and stakeholders.

Education:

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, Data Science, or a related field.

• Master's degree preferred.

Certifications:

• Microsoft Certified: Azure Data Engineer Associate Preferred

• Microsoft Certified: Azure Solutions Architect Expert Preferred

• Microsoft Purview Certification Preferred

• Collibra Ranger Certification Preferred

• SnowPro Core Certification Preferred

• AWS Certified Solutions Architect Associate Preferred

• TOGAF Certification Preferred

• DAMA Certified Data Management Professional (CDMP) Preferred