POSITION TITLE
Lead Data Architect, Modeler
This role is not eligible for employment visa sponsorship.
LOCATION
This role is open to remote candidates residing in the following states: Connecticut, Delaware, Florida, Georgia, Maine, Maryland, Massachusetts, Michigan, New Hampshire, New Jersey, New York, North Carolina, Ohio, Pennsylvania, Rhode Island, South Carolina, Vermont, Virginia, and West Virginia, as well as Washington, D.C. Candidates must be authorized to work in the United States and be able to work primarily during Eastern Time Zone business hours. We will give preference to those within driving distance to Richmond with an expectation that some travel regardless of location will be required
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.
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 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.
Key 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.
Required Qualifications
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.
Preferred Skills
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
Day-to-Day Activities
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.
Success Factors
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.
Employee Benefits & Well-Being
Genworth employees make a difference in people’s lives every day. We’re committed to making a difference in our employees’ lives.
Competitive Compensation & Total Rewards Incentives
Comprehensive Healthcare Coverage
Multiple 401(k) Savings Plan Options
Auto Enrollment in Employer-Directed Retirement Account Feature (100% employer-funded!)
Generous Paid Time Off – Including 12 Paid Holidays, Volunteer Time Off and Paid Family Leave
Disability, Life, and Long Term Care Insurance
Tuition Reimbursement, Student Loan Repayment and Training & Certification Support
Wellness support including gym membership reimbursement and Employee Assistance Program resources (work/life support, financial & legal management)
Caregiver and Mental Health Support Services
ADDITIONAL INFORMATION
National Range: $120,900 - $187,000
Disclaimer: This role is aligned to a national market-based pay range. Actual compensation will vary based on geographic location, experience, skills, and other job-related factors. In addition to base salary, this role is eligible to participate in a bonus incentive plan. Incentive compensation is based on individual and company performance and is not guaranteed.
