Enterprise Data Architect

Location: Richmond, VA – Onsite
Experience: 16+ Years

Job Summary

We are seeking an experienced Enterprise Data Architect to define, govern, and evolve enterprise-wide data architecture across customer, consumer, manufacturing, and supply chain domains.

The ideal candidate will have strong expertise in enterprise data architecture, cloud data platforms, data governance, integration, analytics, and emerging AI technologies. This role will work closely with business and technology leaders to develop scalable, secure, and standardized data solutions.

Key Responsibilities

• 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 architecture governance across multiple programs and initiatives.

• Establish standards for data integration, Master Data Management (MDM), metadata, and data quality.

• Evaluate and standardize cloud-based data and analytics platforms.

• Ensure data architectures meet security, privacy, regulatory, and resiliency requirements.

• Identify opportunities for automation and implement scalable solutions.

• Evaluate and introduce emerging technologies and modern architecture concepts.

• Identify business use cases for data, analytics, AI, and automation.

• Develop architecture patterns supporting enterprise data modernization and digital transformation.

Technology Stack

• Cloud: Azure

• Data Platforms: Snowflake, Azure Synapse, Databricks

• Architecture: Lakehouse, Data Mesh, Event-Driven Architecture

• Integration & Streaming: Kafka, Azure Event Hubs, API Management

• Analytics & BI: Power BI, Tableau, Looker

• Governance & Security: Microsoft Purview, Collibra, IAM, Encryption Frameworks

AI & Advanced Analytics – Preferred

• Enterprise AI and advanced analytics architecture experience.

• Experience with ML platforms, MLOps, and AI lifecycle governance.

• Understanding of Generative AI, LLMs, and responsible AI adoption.

• Experience applying AI to areas such as demand planning, customer insights, intelligent manufacturing, and supply chain optimization.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.

• 12–16+ years of experience in enterprise data architecture.

• Strong experience designing enterprise-scale data architectures.

• Deep knowledge of cloud data platforms and modern data architecture patterns.

• Experience in customer, manufacturing, supply chain, or related enterprise domains.

• Strong understanding of data governance, integration, security, and data quality.

• Excellent stakeholder management and communication skills.

• Demonstrated experience providing architecture governance and technical leadership.

• Ability to evaluate emerging technologies and translate them into practical business solutions.

Preferred Skills

• Enterprise Data Strategy & Roadmap

• Data Governance & MDM

• Cloud Data Architecture

• Data Mesh & Lakehouse Architecture

• Data Engineering & Integration

• Streaming & Event-Driven Architecture

• Data Security & Privacy

• AI/ML Architecture

• Generative AI & LLMs

• MLOps

• Enterprise Architecture Governance

• Business Use Case Development