Enterprise Database Architect

Austin, TX · Hourly

About The Position

Enterprise Database Architect

BizTech Fusion is hiring an Enterprise Database Architect

Experience: 15–18+ Years

Location: Texas — Remote within Texas ONLY

Employment Type: Contract / C2C

Interview: Video Interview

Work Authorization: Must be eligible to work in the U.S.

Position Overview

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.

Required 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
  • 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

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