Lead Data Architect, Modeler

Location: Remote candidates residing in Connecticut, Delaware, Florida, Georgia, Maine, Maryland, Massachusetts, Michigan, New Hampshire, New Jersey, New York, North Carolina, Ohio, Pennsylvania, Rhode Island, South Carolina, Vermont, Virginia, West Virginia, and Washington, D.C. Must be authorized to work in the United States and able to work primarily during Eastern Time Zone business hours. Preference given to those within driving distance to Richmond, with hybrid in‑office required if within 50 miles of the Richmond or Lynchburg, VA office.

About the role

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 have enough detail on how data is collected, stored, integrated, transformed, and published so other teams can implement the blueprints. The blueprints you build will also contain capability frameworks so the how data is collected, stored, integrated, transformed, and published is done in a consistent manner across teams when appropriate and also with pre built components or templates to further enable a consistent approach and enable more cost effective and faster execution of data product delivery.

Responsibilities

• Establish enterprise data models including an enterprise insurance data model that is followed by different 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 the technology platforms, data pipelines, data models, ML and AI applications, data governance platforms, data security, and hyper scaler cloud services.
• Align and leverage data governance interoperability work such as leveraging data stewards for defining data model attribute names and definitions. Also, work with the data governance team on metadata information about the data model that is needed for data governance management.
• Data modeling: Develop conceptual, logical, and physical data models for business intelligence, AI and ML requirements, and operational data use cases.
• Performance Optimization: Monitor and optimize data models for query performance and scalability.
• Collaborating with data modelers on how their data model scope should integrate into the enterprise insurance data model.
• Participating in meetings with business stakeholders to understand analytical or operational data needs so the best data modeling approach is selected.
• Designing and documenting data models, including entity relationships and dimensional models.
• Collaboration and Communication: Serve as a bridge between technical teams and business teams, clearly communicating the value and limitations of data models so adoption of the data models occurs.
• Data model training activities so business users can effectively build required queries against the model.
• Collaborating with data engineers to create data pipelines to populate the data models.

Requirements

• Bachelor’s degree in computer science, Information Systems, Data Science, Mathematics, or related field. Master’s degree preferred.
• Minimum 3 years of experience in data modeling in a Lakehouse analytics environment.
• Proficiency in a