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# Enterprise Data Architect

- **Company:** Circle Graphics, Inc.
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Information Systems, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Migration, Data Warehousing, Graph Database, Interoperability, Metadata, MongoDB, Unstructured Data, Enterprise Data Management, Google Cloud, Cloud Platform System, Snowflake, Data Layers, Information Technology, Api Design, Legacy Systems, Databricks
- **Published:** August 11, 2026
- **Apply:** https://www.dice.com/job-detail/b4f4fafe-0bf3-43c1-ac6e-351526d8974a

## About the Role

Bachelor's degree in Computer Science, Information Systems, or related field.
10+ years of experience in data, information, or enterprise architecture.
8+ years of hands-on experience with data architecture, data modeling, data engineering, data warehouses/marts, and/or MDM.
5+ years experience with modern data platforms such as Snowflake, Databricks, MongoDB and cloud environments (AWS, Azure, or Google Cloud Platform).
Experience with data governance, data quality, metadata, lineage, security, privacy, and regulatory requirements.
Experience supporting large-scale modernization or digital transformation initiatives.
Strong communication and stakeholder management skills with the ability to lead without direct authority.
Preferred
Experience in Public Sector, Healthcare, or Financial Services.
Experience with structured/unstructured data, semantic layers, knowledge graphs, or AI data architectures.
Previous experience as an Enterprise Data Architect, Principal Architect, Enterprise Information Architect, or Solution Architect.

## Description

The Enterprise Data Architect will define and evolve the enterprise data architecture and reusable data products to support modernization, digital transformation, and AI initiatives. This role partners with business, product, engineering, cloud, and enterprise technology teams to establish data domains, models, standards, quality, governance, and reusable information assets., Define conceptual, logical, and canonical data models and enterprise information standards.
Establish data domains, ownership, stewardship, relationships, and reusable data products.
Analyze legacy systems and support modernization, data migration, and target-state architecture.
Define data product schemas, interfaces, metadata, quality requirements, and data contracts.
Establish standards for data governance, cataloging, lineage, quality, security, privacy, and interoperability.
Partner with cloud, integration, engineering, and data teams to implement enterprise data solutions.
Promote API-first and reusable data architecture to reduce duplication and data silos.
Ensure enterprise data is discoverable, governed, and AI-ready, including support for semantic layers and knowledge graphs.
Lead through influence and collaborate across multiple business domains and stakeholders.


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