Enterprise Database Architect

Role Description

BizTech Fusion is looking for an experienced Enterprise Database Architect with strong expertise in Enterprise MDM and Data Catalog implementation. The ideal candidate will have a minimum of 7+ years of hands-on experience implementing MDM/Data Catalog solutions and will bridge enterprise data architecture, data engineering, governance, and AI consumption needs.

The Database Architect will implement an enterprise-wide Data Catalog/MDM solution covering both structured and unstructured data, and establish the semantic layer and data lineage required for AI/ML and Generative AI discovery and enablement. The role will ensure that high-quality, well-documented, governed, and trusted data assets are available for analytics, machine learning, and generative AI use cases. The successful candidate will also establish continuous processes to keep catalog/MDM solutions updated as data and systems change while maintaining data quality, consistency, lineage, classification, and governance.

Key Responsibilities

• Enterprise Data Modeling, Semantics & AI Enablement
  • Develop conceptual, logical, and physical data models across multiple enterprise domains.
  • Map data transformations and integrations and drive clarity across systems.
  • Reverse-engineer legacy data structures to modernize, streamline, and rationalize system designs.
  • Use ER/Studio and model automation to establish enterprise modeling standards and support performance.
  • Govern design-to-implementation alignment with engineering teams.
  • Expand taxonomy and ontology usage across enterprise domains.
  • Apply semantic tagging to improve data discovery, trust, and reuse.
  • Align semantic attributes with lineage and data classification rules.
  • Design and support semantic/context layers for AI/ML and Generative AI use cases.
• Data Governance, Metadata & Catalog Management
  • Implement and maintain enterprise Data Catalog and MDM solutions.
  • Maintain and enrich enterprise data dictionaries.
  • Automate metadata ingestion, scanning, and discovery processes.
  • Apply data lineage, classification, governance, and security standards.
  • Work with platforms such as Microsoft Purview, Collibra, Alation, or equivalent enterprise catalog solutions.
  • Connect Data Catalog platforms with BI and ETL/ELT pipelines.
  • Expand business glossary coverage in collaboration with data stewards.
  • Implement catalog APIs for programmatic queries, updates, and automation.
  • Train business and technical users on enterprise catalog practices.
  • Establish and monitor metadata quality KPIs.
• Data Strategy & Readiness
  • Translate business requirements into structured data models and metadata deliverables.
  • Prioritize data modeling and governance activities with product owners and stakeholders.
  • Provide project status, risks, dependencies, and implementation updates.
  • Support business-led analytics and enterprise data stewardship activities.
  • Ensure enterprise data assets are prepared for analytics, AI/ML, and GenAI consumption.
• Team Enablement & Knowledge Transfer
  • Facilitate enterprise data architecture and model reviews.
  • Maintain data architecture standards, templates, and documentation.
  • Support cross-enterprise data stewardship and governance routines.
  • Develop training materials and onboarding guides for business and technical users.
  • Provide knowledge transfer to engineering, governance, analytics, and business teams.

Qualifications

• 15–18+ years of overall IT experience with significant enterprise data/database architecture experience.
• 7+ years of hands-on Enterprise MDM and/or Data Catalog implementation experience — REQUIRED.
• Strong experience as an Enterprise Database Architect, Data Architect, Data Modeler, or DBA.
• Hands-on experience with Oracle and SQL Server RDBMS.
• Expertise with enterprise Data Catalog/MDM platforms such as Microsoft Purview, Collibra, Alation, or other comparable enterprise catalog/MDM platforms.
• Experience with AI/ML technologies and semantic/context layer design and integration.
• Strong understanding of enterprise data modeling, metadata management, and data architecture.
• Experience with AWS and Azure cloud technologies.
• Experience with cloud data platforms, including AWS Data Lake.
• Strong understanding of data governance, classification, security, and stewardship.
• Experience with data lineage, integration, and transformation technologies such as Informatica, Fivetran, or equivalent.
• Experience designing APIs for metadata harvesting, automation, and event-driven integration.
• Experience integrating enterprise data catalogs with data pipelines and BI platforms.
• Experience with enterprise taxonomy, ontology, semantic tagging, and business glossaries.
• Experience with GitHub.

Preferred Qualifications

• Experience with vector databases.
• Experience with feature stores.
• Strong Python scripting experience for automation and data engineering.
• Previous experience working with Texas state government agencies.
• Experience enabling enterprise data for Generative AI, AI agents, machine learning, or other AI applications.

Candidate Requirements

• Candidates must currently reside in Texas.
• Valid Texas Driver License is required.
• This is a remote position within Texas only.
• Candidates outside Texas will not be considered.
• Must be available for a video interview.

Core Skills

• Enterprise Data Architecture
• MDM
• Data Catalog
• Microsoft Purview
• Collibra
• Alation
• Oracle
• SQL Server
• Data Modeling
• ER/Studio
• Data Governance
• Metadata Management
• Data Lineage
• Data Classification
• Data Quality
• Semantic Layer
• Ontology
• Taxonomy
• AI/ML
• GenAI
• AWS
• Azure
• AWS Data Lake
• Informatica
• Fivetran
• API Design
• Metadata Harvesting
• Event-Driven Integration
• Vector Databases
• Feature Stores
• Python
• GitHub