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Sr Manager - Data Architecture

Job in Richmond, Henrico County, Virginia, 23214, USA
Listing for: Genworth Financial, Inc.
Full Time position
Listed on 2026-05-31
Job specializations:
  • IT/Tech
    Data Engineer, Data Analyst, Data Science Manager
Salary/Wage Range or Industry Benchmark: 120000 - 195000 USD Yearly USD 120000.00 195000.00 YEAR
Job Description & How to Apply Below

Position Title

Sr Manager – Data Architecture

Location

Virginia (Richmond or Lynchburg, VA) – Hybrid or remote within Eastern or Central Standard Time states and territories as listed.

Position Overview

You will be designing the structural blueprints for Genworth’s data systems, ensuring that the data is secure, accessible, and available so that business goals and requirements are met with your blueprints. The blueprints will contain enough detail on how data is collected, stored, integrated, transformed, and published so other teams can implement the blueprints. They will also contain capability frameworks to promote consistent and cost‑effective data product delivery.

Key Responsibilities
  • Establish enterprise data models, including an enterprise insurance data model followed by build and vendor partners.
  • Define data domains and structures based on business requirements.
  • Define and enable consistent data designs so data solution construction and data user experience is consistent.
  • Create decision trees to define what must be consistent based on the situation and requirements.
  • Define and design interoperability across data solutions, including technology platforms, data pipelines, data models, ML and AI applications, data governance platforms, data security, and cloud services.
  • Align and leverage data governance interoperability work, such as utilizing data stewards for defining data model attribute names and definitions.
  • Work with the data governance team on metadata information needed for data governance management.
  • Develop conceptual, logical, and physical data models for business intelligence, AI and ML requirements, and operational data use cases.
  • Monitor and optimize data models for query performance and scalability.
Qualifications

Required:

  • Bachelor’s degree in computer science, Information Systems, Data Science, Mathematics, or a related field (Master’s degree preferred).
  • Minimum 3 years of experience in data modeling in a Lakehouse analytics environment.
  • Proficiency in a data modeling tool such as ER Studio.
  • Experience with big data technologies and platforms (e.g., Data Bricks, Spark, AWS, Azure).
  • Expert level in DDL and SQL development.
  • Experience working with data governance, quality frameworks, and metadata management, and understanding how this connects to data modeling practices.
  • Strong analytical, problem‑solving, and critical thinking skills.
  • Excellent communication and interpersonal abilities.
  • Ability to work independently and collaborate in a cross‑functional team environment.
Preferred Skills
  • Understanding of PII and PHI data governance and security.
  • Experience working on an agile team using agile tools and practices.
  • Knowledge of Azure and AWS services relevant to data architecture and services.
  • Knowledge of data lakes and data pipelines that transform raw data into the required format.
  • Experience with data taxonomies in insurance.
Day-to-Day Activities
  • Collaborate with data modelers on integrating their scope into the enterprise insurance data model.
  • Participate in meetings with business stakeholders to understand analytical or operational data needs and select appropriate data modeling approaches.
  • Design and document data models, including entity relationships and dimensional models.
  • Serve as a bridge between technical teams and business teams, communicating the value and limitations of data models to drive adoption.
  • Conduct data model training activities so business users can build queries against the model.
  • Collaborate with data engineers to create data pipelines that populate the data models.
Success Factors
  • Business Acumen – understand insurance business processes, goals, and pain points to design data models that solve real-world problems.
  • Technical Expertise – deep familiarity with modern data modeling techniques, database management, and analytics platforms.
  • Adaptability – thrive in a fast‑paced, dynamic environment and pivot between projects quickly.
Compensation

Base salary range: $120,000 – $195,000 (P4). Eligibility to participate in an incentive plan with a target earning opportunity of 15% based on performance.

Benefits
  • Competitive Compensation & Total Rewards incentives.
  • Comprehensive healthcare…
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