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# Enterprise Data Architect

- **Company:** Capgemini
- **Location:** New Brunswick, United States
- **Experience:** Expert
- **Salary:** $125,000.0 - $175,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Information Systems, Data as a Services, Data Architecture, Information Engineering, Data Governance, Machine Learning, Meta-Data Management, Cloud Services, Software Engineering, Enterprise Data Management, Generative AI, Information Technology, Data Management, Databricks
- **Published:** October 9, 2026
- **Apply:** https://www.dice.com/job-detail/1544fa64-7189-4616-a4d0-7f6497db2d51

## About the Role

10+ years of experience in data architecture, data engineering, or enterprise data management.

Deep expertise in Enterprise Data Architecture, Data Modeling, and modern cloud data platforms.

Hands-on experience designing and implementing Databricks Lakehouse architectures.

Strong experience with Microsoft Azure data services and cloud-native data solutions.

Proven experience guiding engineering teams through Bronze, Silver, and Gold Lakehouse implementations.

Strong knowledge of data governance, data quality, metadata management, and master data management principles.

Education:

 * Bachelor's or Master's degree in Computer Science, Software Engineering, Information Systems, Business Administration, or a related field.

## Description

Define and lead the enterprise data architecture strategy, standards, and roadmap aligned with business and technology objectives.

Provide technical leadership and mentorship to Data Engineers, Data Modelers, and other data professionals throughout the solution lifecycle.

Architect and oversee the implementation of modern Lakehouse solutions utilizing Databricks and Microsoft Azure technologies.

Design and govern data architectures across Bronze, Silver, and Gold layers to ensure scalable, reliable, and business-ready data products.

Establish and enforce data governance frameworks, metadata management practices, and enterprise data standards.

Partner with business stakeholders, product owners, and technology leaders to understand requirements and translate them into scalable architectural solutions.

Serve as the primary technical advisor for data platform initiatives, proactively identifying risks, removing technical blockers, and accelerating delivery.

Collaborate with AI, analytics, and reporting teams to ensure data platforms support advanced analytics, machine learning, and Generative AI use cases.