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# Data Architect (Hybrid - Cloud and On-Prem)

- **Company:** Guidehouse Inc.
- **Location:** McLean, VA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Meta-Data Management, Data Ingestion, Snowflake, HybridCloud, AI Platforms
- **Published:** August 3, 2026
- **Apply:** https://www.careerboard.com/us/en/find-jobs-in-United-States/-4A2285052A3355665A/

## About the Role

* US Citizenship.is required
 * Bachelor's degree is required
 * Minimum of ten (10) years of experience in data architecture, data engineering, or related technical roles.
 * Strong experience designing data architectures in AWS and Snowflake environments.
 * Experience with data modeling (logical and physical) and enterprise data design.
 * Experience supporting data governance and stakeholder engagement activities.
 * Ability to work in a hybrid environment in the DC area.

What Would Be Nice to Have

 * Certifications in Snowflake, AWS, or data architecture disciplines.
 * Experience supporting enterprise analytics or AI platforms.
 * Prior experience supporting financial services or regulatory organizations.

## Description

Guidehouse is seeking a Data Architect to design, implement, and govern enterprise data architectures that support analytics, reporting, and AI use cases. This role provides architectural leadership across data modeling, data engineering, and data governance, and works closely with cloud architects, engineers, and business stakeholders., * Design and maintain logical and physical data models supporting enterprise analytics and AI initiatives.

 * Define and oversee enterprise data architecture standards, patterns, and best practices.
 * Lead solution architecture for data ingestion, transformation, storage, and consumption layers.
 * Provide technical leadership across AWS and Snowflake data environments.
 * Support data governance initiatives including metadata management, data quality, lineage, and stewardship.
 * Translate business and regulatory requirements into scalable data architecture solutions.
 * Partner with delivery teams during implementation to ensure architectural alignment and quality.


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