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Enterprise Data Architect (MDM /Data Catalog/AI)
Neos ConsultingAustin, TX🇺🇸United StatesPosted 10 Aug 2026
Quick Overview
Work Type
Hybrid
Level
Mid Senior
Job Description
City : Austin
State : Texas
Neos is Seeking an Enterprise Data Architect (MDM/ Data Catalog/AI) for a long-term contract role with our client in Austin, TX.
***REMOTE (TEXAS) - ONLY CANDIDATES CURRENTLY RESIDING IN TEXAS WILL BE CONSIDERED***
No calls, no emails, please respond directly to the "apply" link with your resume and contact details.
Description of Services
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
Data Governance, Metadata & Catalog Management
Data Strategy & Readiness
Team Enablement & Knowledge Transfer
Candidate Skills and Qualifications
Requirements
Preferred Qualifications
#DICE
#LI-MB
State : Texas
Neos is Seeking an Enterprise Data Architect (MDM/ Data Catalog/AI) for a long-term contract role with our client in Austin, TX.
***REMOTE (TEXAS) - ONLY CANDIDATES CURRENTLY RESIDING IN TEXAS WILL BE CONSIDERED***
No calls, no emails, please respond directly to the "apply" link with your resume and contact details.
Description of Services
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
- Develops conceptual, logical, physical models across domains.
- 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.
Data Governance, Metadata & Catalog Management
- 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.
Data Strategy & Readiness
- 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.
Candidate Skills and Qualifications
Requirements
- 7 years Required - Working as an Enterprise Database Architect experience with MDM/Data Catalog implementation.
- 4 years Required - Experience as a Data Modeler/DBA with Oracle and SQL Server RDBMS.
- 4 years Required - Expertise in various enterprise data catalog platforms like Microsoft Purview, Collibra, Alation, etc.
- 3 years Required - Experience in AI/ML technologies and semantic/context layer design and integration.
- 3 years Required - Experience with cloud technologies and tools in AWS and Azure including data platforms like AWS Data Lake.
- 3 years Required - Data Governance, classification and security.
- 2 years Required - Data Lineage, Integration and Transformation tools like Informatica, Fivetran, etc.
- 2 years Required - Experience in API design in metadata harvesting, automation and event driven integration.
Preferred Qualifications
- 2 years Preferred - Vector databases, feature stores experience.
- 2 years Preferred - Experience in scripting using Python.
- 2 years Preferred - Experience working with Texas state government agencies.
- 1 year Preferred - Experience using GitHub.
#DICE
#LI-MB
Skills
Oracle
SQL
SQL Server
AWS
ETL
Machine Learning
Azure
Generative AI
Python
Unity
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