The Database Architect will implement an enterprise wide Data Catalog/MDM solution covering both structured and unstructured data, and setup and configure the semantic layer and lineage needed for AI tools discovery/enablement. The ideal candidate will bridge data engineering, governance, and AI consumption needs to ensure high-quality, well-documented data assets are available for analytics, machine learning, and generative AI use cases. A continuous process should be established to keep the catalog/mdm solution updated when changes are made, and ensure data quality and consistency is maintained.
This position will perform the following duties, working across various teams.
Enterprise Data Modeling, Semantics & AI Enablement
- Maps transformations & integrations, and drive clarity across systems.
- Reverse-engineers legacy data structures to modernize, streamline, and rationalize system designs.
- Uses ER/Studio & model automation to ensure standards and performance.
- Governs design-to-implementation alignment with engineering.
- Expands taxonomy and ontology usage across domains.
- Applies semantic tagging to improve discovery, trust, and reuse.
- Aligns semantic attributes with lineage & classification rules.
- Maintains and enriches data dictionaries while automating metadata ingestion and scanning processes.
- Applies lineage and classification standards (Purview/Unity Catalog).
- Connects catalog to BI and ETL/ELT pipelines.
- Expands glossary coverage with stewards.
- Implements catalog APIs for programmatic queries/updates.
- Trains users on catalog practices and continuously monitors metadata quality KPIs.
- Translates business needs into structured data designs and metadata deliverables
- Prioritizes modeling/governance work with product owners.
- Provides status & risk updates; manage dependencies.
- Supports business-led analytics and stewardship routines.
Team Enablement & Knowledge Transfer
- Facilitates design/model reviews while maintaining standards and templates.
- Supports cross-enterprise stewardship and governance routines.
- Creates training materials and onboarding guides for business users.
II. CANDIDATE SKILLS AND QUALIFICATIONS
Candidates that do not meet or exceed the minimum stated requirements (skills/experience) will be displayed to customers but may not be chosen for this opportunity.
Years
Required/Preferred
Experience
7
Required
Working as an Enterprise Database Architect experience with MDM/Data Catalog implementation
4
Required
Experince as a Data Modeler/DBA with Oracle and SQL Server RDBMS
4
Required
3
Required
Experience in AI/ML technologies and semantic/context layer design and integration.
3
Required
Experience with cloud technologies and tools in AWS and Azure including data platforms like AWS Data Lake
3
Required
Data Governance, classification and security
2
Required
Data Lineage, Integration and Transformation tools like Informatica, Fivetran, etc.
2
Required
Experience in API design in metadata harvesting, automation and event driven integration
2
Preferred
2
Preferred
Experience in scripting using Python preferred.
2
Preferred
Experience working with Texas state government agencies preferred.
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