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# Data Architect

- **Company:** Sparks Group
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Engineering, Data as a Services, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Machine Learning, Enterprise Data Management, Data Lakes, Data Analytics, Data Management
- **Published:** July 2, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=44f8b59f9f0230ad

## About the Role

* 8+ years of experience in data architecture, data engineering, cloud architecture, or related technical disciplines with demonstrated ownership of enterprise data platform design.
 * Strong experience with AWS, Azure, and/or GCP, along with data warehouses, data lakes, lakehouses, ETL/ELT concepts, and modern cloud-native data services.
 * Ability to operate as a client-facing advisor while maintaining sufficient hands-on technical depth to guide architecture decisions and support implementation teams.

## Description

Job Summary/Company: Our client is seeking a Data Architect to design scalable, AI-ready data platforms that support analytics, machine learning, and enterprise modernization initiatives. This role will serve as both a technical architect and advisor, helping organizations design cloud-based data environments that enable successful AI and data-driven business outcomes.
Responsibilities

 * Design enterprise data architectures including data lakes, lakehouses, cloud repositories, and hybrid environments that support analytics, machine learning, and AI initiatives.
 * Lead architecture assessments, develop target-state designs, and provide strategic guidance on cloud platforms, data governance, integration patterns, and data modernization efforts.
 * Partner with data engineers, cloud engineers, and AI teams to ensure data environments are scalable, secure, well-governed, and optimized for future AI use cases.


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