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# Enterprise Data Architect

- **Company:** Capgemini
- **Location:** Bridgewater, NJ, United States
- **Salary:** $141,420.0 - $235,035.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Architectural Patterns, Cloud Database, Data Integration, Identity and Access Management, Metadata, Power BI, Data Mesh, Azure Machine Learning, Data Streaming, Tableau (Software), Enterprise Data Management, Azure Service Bus, Large Language Models, Snowflake, Generative AI, Event Driven Architecture, Microsoft Fabric, Information Technology, Collibra, Data Analytics, Apache Kafka, Data Management, Machine Learning Operations, Azure Synapse Analytics, Looker Analytics, Api Management, Databricks
- **Published:** October 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ae25ac8e9caad705

## About the Role

* Bachelor's or Master's degree in Computer Science, Engineering, or related field
 * 12+ years of experience in enterprise data architecture
 * Deep experience with customer, manufacturing, or supply chain domains
 * Strong stakeholder influence and architecture governance leadership.
 * Architecture Patterns: Lakehouse, Data Mesh, Event-Driven Architecture
 * Data Platforms: Snowflake, Azure Synapse, Databricks
 * Integration & Streaming: Kafka, Event Hubs, API Management
 * Analytics & BI: Power BI, Tableau, Looker
 * Governance & Security:Microsoft Purview, Collibra, IAM, encryption frameworks

## Description

Capgemini is seeking an Enterprise Data Architect to join our I&D team in Richmond, VA. The successful candidate will lead the development, governance, and evolution of the enterprise data architecture strategy across customer, consumer, manufacturing, and supply chain domains. This role is responsible for aligning business objectives with data platforms, analytics capabilities, and emerging AI solutions, while promoting scalability, security, and enterprise-wide standardization.

Your role

 * Define enterprise data architecture principles, standards, and target-state roadmaps
 * Design end-to-end data architectures covering ingestion, storage, processing, analytics, and AI
 * Partner with business, analytics, and technology leaders to translate strategic objectives into scalable data solutions
 * Provide architectural governance across multiple programs and initiatives
 * Establish standards for data integration, master data management (MDM), metadata, and data quality
 * Evaluate, select, and standardize cloud-based data and analytics platforms
 * Ensure compliance with security, privacy, regulatory, and resiliency requirements
 * Identify and Implement Automation
 * Bring in new or Emerging Technology concepts and implement
 * Defining enterprise AI and advanced analytics architectures
 * Experience with ML platforms, MLOps, and AI lifecycle governance
 * Understanding of generative AI, LLMs, and responsible AI adoption
 * Applying AI to demand planning, customer insights, intelligent manufacturing, and supply chain optimization