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# Lead Data Architect

- **Company:** Genworth Financial, Inc.
- **Location:** Richmond, VA, United States
- **Experience:** Expert
- **Salary:** $165,000.0 - $195,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Business Analytics Applications, Microsoft Azure, Big Data, Data Architecture, Data Governance, Extract Transform Load (ETL), Data Warehousing, Relational Databases, Meta-Data Management, Cloud Services, Data Management, Video Streaming
- **Published:** September 8, 2026
- **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=2961203805-2

## About the Role

* Data architecture
 * Data modeling (conceptual, logical, physical)
 * Cloud data platforms (AWS/Azure/GCP)
 * Data warehousing and ETL/ELTSQL and relational databases
 * Big data and streaming technologies
 * Data governance and metadata management
 * Data security and privacy (e.g., HIPAA/PII practices)
 * BI/reporting and analytics platforms
 * Financial services/insurance domain knowledge

## Description

Genworth is seeking a Lead Data Architect to shape the enterprise data strategy powering our long-term care, mortgage insurance, and annuity businesses. You will define data architectures, models, and integration standards that enable secure, trusted, and accessible data across the organization. Partnering with engineering, analytics, and business stakeholders, you'll modernize our data platforms, support regulatory and reporting needs, and drive cloud and real-time capabilities. In this role, you'll mentor technical teams and help build innovative solutions that support families' long-term financial security., * Lead the design and governance of enterprise data architecture to support Genworth's insurance and financial products

 * Define data models, integration patterns, and standards for analytics, reporting, and regulatory needs
 * Partner with engineering, data science, and business teams to translate requirements into scalable data solutions
 * Modernize data platforms, enabling cloud, real-time, and self-service data capabilities
 * Ensure data quality, security, privacy, and lineage across systems and domains
 * Mentor data engineers and analysts, promoting best practices and continuous improvement


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