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# Enterprise Data Architect

- **Company:** Infoorigin inc -
- **Location:** Harrisburg, PA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Data Architecture, Information Engineering, Data Governance, Data Mart, Data Migration, Data Warehousing, Database Design, Graph Database, Interoperability, Logical Data Models, Metadata, MongoDB, Enterprise Data Management, Google Cloud, Cloud Platform System, Snowflake, Data Layers, Api Design, Databricks
- **Published:** August 11, 2026
- **Apply:** https://www.dice.com/job-detail/1f7f751a-5eea-45e9-9b21-e366c295eab9

## About the Role

* 10+ years of experience in Data Architecture, Information Architecture, or Enterprise Architecture.
 * 8+ years of hands-on data architecture, data engineering, database design, and data modeling experience.
 * Experience with data warehouses/data marts and MDM concepts/tools.
 * 5+ years with platforms such as Snowflake, Databricks, MongoDB, and cloud ecosystems including AWS, Azure, or Google Cloud Platform.
 * Strong experience with data governance, data quality, metadata, lineage, security, privacy, and regulatory requirements.
 * Experience supporting large-scale modernization or digital transformation initiatives.
 * Strong communication, stakeholder management, and problem-solving skills.
 * Public Sector, Healthcare, or Financial Services experience preferred.

## Description

We are seeking an experienced Enterprise Data Architect to define enterprise data architecture and build reusable data products supporting modernization, analytics, and AI initiatives. The architect will work with business, product, engineering, cloud, and technology teams to create data models, improve data quality, establish governance, and prevent data silos., * Define conceptual/logical data models, canonical models, and enterprise data standards.

 * Design reusable data products, schemas, metadata, and ownership models.
 * Support legacy modernization, data migration, and target architecture.
 * Establish data governance, quality, lineage, catalog, security, and interoperability standards.
 * Partner with cloud, integration, engineering, and data teams to implement enterprise data solutions.
 * Support API-first approaches, semantic layers, knowledge graphs, and future AI capabilities.


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