Database Architect

Digerati Systems Inc.; Austin (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Digerati Systems Inc. is seeking an Enterprise Database Architect to design and implement an enterprise Data Catalog/MDM, bridging data engineering, governance and AI consumption to deliver high-quality, well-documented data assets for analytics and generative AI use cases.

Responsibilities include modeling across domains, applying semantic tagging, managing lineage (Purview/Unity Catalog), training users, and collaborating with product owners to prioritize work while maintaining metadata

Qualifications

• 7+ years as Enterprise Database Architect with MDM/Data Catalog implementation.
• 4+ years Data Modeling/DBA with Oracle and SQL Server RDBMS.
• 3+ years AI/ML, semantic layer design and integration.
• 3+ years Cloud (AWS/Azure) data platforms including data lakes.
• 2+ years Data Governance, classification and security.
• 2+ years Data Lineage, Integration and Transformation tools (Informatica, Fivetran).
• 2+ years API design for metadata harvesting, automation and event-driven integration.
• Python scripting experience preferred.

Responsibilities

• Enterprise Data Modeling, Semantics & AI Enablement across domains.
• Governs design-to-implementation alignment with engineering.
• Connects catalog to BI and ETL/ELT pipelines; expands taxonomy/ontology.
• Maintains metadata dictionaries; automates ingestion and scanning processes.
• Trains users on catalog practices and monitors metadata quality KPIs.
• Supports cross-enterprise stewardship, governance routines, and knowledge transfer.

Skills

Enterprise DB Architect

Data Modeling / DBA

AI/ML semantic layer

Cloud AWS/Azure data platforms

Data Governance & Security

Data Lineage & ETL tools

API design for metadata harvesting

Python scripting

Tools

Informatica

Fivetran

Job description

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.