> Markdown version of [/jobs/ext/3030104-lead-data-architect](https://www.wearedevelopers.com/jobs/ext/3030104-lead-data-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Architect - **Company:** Genworth Financial, Inc. - **Location:** Richmond, VA, United States - **Experience:** Expert - **Salary:** $120,900.0 - $187,000.0 - **Contract:** Permanent contract - **Skills:** Query Performance, Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Microsoft Azure, Big Data, Cloud Computing, Cyber Security, Information Systems, Data Architecture, Data Governance, Data Security, Data Structures, Data Systems, Database Analysis, Database Development, Dimensional Modeling, Entity Relationship Models, Design of User Interfaces, Human-Computer Interaction, Interoperability, Machine Learning, Metadata, Meta-Data Management, Operational Data Store, Performance Tuning, Cloud Services, SQL Databases, Apache Spark, Data Lakes, Information Technology, Data Management, Physical Data Models, Data Pipelines, Databricks - **Published:** September 22, 2026 - **Apply:** https://www.careerbuilder.com/job-details/lead-data-architect-richmond-va--da397512-a015-4428-827c-e7684cee44fb ## About the Role 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., * 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, * 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., Amazon Web Services (AWS), Analysis Skills, Architectural Services, Artificial Intelligence (AI), Big Data, Blueprints, Business Intelligence, Business Processes, Business Skills, Cloud Computing, Communication Skills, Compensation and Benefits, Computer Science, Construction, Cross-Functional, Customer Support/Service, Data Collection, Data Description Language (DDL), Data Management, Data Modeling, Data Modeling Tools, Data Science, Data Structures, DataArchitect Data Modeling Tool, Database Administration, Database Analysis, Dimensional Modeling, Diversity, Documentation, Embarcadero ER/Studio, Entity Relationship Diagram (ERD), Healthcare, Information Technology & Information Systems, Information/Data Security (InfoSec), Insurance, Interoperability, Interpersonal Skills, Legal, Mathematics, Metadata, Microsoft Windows Azure, Operational Audit, Performance Analysis, Performance Modeling, Performance Tuning/Optimization, Problem Solving Skills, Psychiatry and Mental Health, Reimbursement, SQL (Structured Query Language), Student Loans, Taxonomies, Tuition Reimbursement, Use Cases, User Interface/Experience (UI/UX), Volunteer Experience, Willing to Travel ## Description 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., * 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. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) ## Related Articles - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Analyst Salary in Switzerland](https://www.wearedevelopers.com/magazine/276-data-analyst-salary-in-switzerland)