Lead Data Architect, Modeler

At Genworth, we empower families to navigate the aging journey with confidence. We are compassionate, experienced allies for those navigating care with guidance, products, and services that meet families where they are. Further, we are the spouses, children, siblings, friends, and neighbors of those that need care—and we bring those experiences with us to work in serving our millions of policyholders each day.

We apply that same compassion and empathy as we work with each other and our local communities. Genworth values all perspectives, characteristics, and experiences so that employees can bring their full, authentic selves to work to help each other and our company succeed. We celebrate our diversity and understand that being intentional about inclusion is the only way to create a sense of belonging for all associates. We also invest in the vitality of our local communities through grants from the Genworth Foundation, event sponsorships, and employee volunteerism.

Our four values guide our strategy, our decisions, and our interactions:
• Make it human. We care about the people that make up our customers, colleagues, and communities.
• Make it about others. We do what's best for our customers and collaborate to drive progress.
• Make it happen. We work with intention toward a common purpose and forge ways forward together.
• Make it better. We create fulfilling purpose-driven careers by learning from the world and each other.

POSITION TITLE

Lead Data Architect, Modeler

*Hybrid in-office would be required if you reside within 50 miles of our Richmond or Lynchburg, VA office. Required in-office days are Tuesdays, Wednesdays and Thursdays with working hours targeting our core business hours of 9am-5pm EST.

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. 

• →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.

• Bachelor’s degree in computer science, Information Systems, Data Science, Mathematics, or related field. Master’s degree preferred.
• Technical qualifications
  • 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., DataBricks, Spark, AWS, Azure).
  • Expert level in DDL and SQL development
  • Experience working with data governance, quality frameworks, and metadata management, and how this connects to data modeling practices and needs.
• Overall qualifications
  • Strong analytical, problem-solving, and critical thinking skills needed for data modeling
  • Excellent communication and interpersonal abilities.
  • Ability to work independently and collaboratively in a cross-functional team environment.

• Understanding of PII and PHI data and how they are governed and secured
• Experience working on an agile team using agile tools, and associated practices.
• Data taxonomies in insurance
• 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 data that is required

• 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.

• Business Acumen: Ability to 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: Ability to thrive in a fast-paced, dynamic environment and quickly pivot between projects.