Aptive is seeking a highly experienced and strategic Data Architect to support the Veterans Health Administration (VHA) in advancing operational performance, healthcare delivery, and digital transformation efforts under the Electronic Health Record Modernization (EHRM) program. This role will be instrumental in designing, developing, and governing the data architecture that supports analytics platforms, clinical systems, and enterprise reporting for different VHA initiatives.

Working closely with the Reporting and Analysis team as well as the Tooling Team (PowerBi, PowerApps, ServiceNow, etc.), the Data Architect will serve as the lead for designing scalable, secure, and sustainable data solutions. The architect will ensure alignment between business goals and technical infrastructure, facilitate data interoperability across different VHA systems, and provide stewardship over data architecture standards and best practices.

• Design and maintain enterprise data architecture to support EHRM reporting platforms, data integration pipelines, and analytical tools.
• Develop and maintain logical and physical data models, ensuring scalability, consistency, and alignment with VHA standards.
• Define and enforce data governance practices including metadata management, data lineage, and master data management strategies.
• Collaborate with data scientists, developers, and analysts to ensure consistent data availability, quality, and structure for analytics and decision-making.
• Establish and lead data integration frameworks, including APIs, ETL processes, and interoperability standards across multiple systems (e.g., clinical, operational, performance).
• Partner with technical and functional stakeholders to translate business requirements into sound data design strategies.
• Define and oversee data quality and integrity frameworks, including data validation rules and automated checks across the data lifecycle.
• Participate in sprint planning, backlog grooming, and Agile ceremonies to prioritize and deliver architectural enhancements.
• Evaluate and recommend new technologies, platforms, or methods that enhance data architecture and overall performance.

• Bachelor's or master's degree in computer science, Data Engineering, Information Systems, or a related technical field.
• 10+ years of relevant experience in data architecture, data engineering, or enterprise data systems.
• Proven experience with data modeling, enterprise data warehousing, and cloud-based data infrastructure (e.g., Azure, AWS, GCP).
• Deep knowledge of data governance, metadata management, and data lineage frameworks.
• Proficiency in database technologies (e.g., SQL Server, PostgreSQL, Oracle) and modern data platforms.
• Demonstrated experience designing data architecture with compute performance in mind, including the ability to manage and optimize compute resources and operationalize scalable data processing solutions.
• Experience in designing or supporting business intelligence environments.
• Ability to convey complex technical solutions to diverse stakeholders, including executive and non-technical audiences.
• Advanced proficiency with Microsoft Office tools and collaboration platforms.
• Experience in fast-paced environments requiring high attention to detail.
• Ability to obtain and maintain public trust clearance.

• Familiarity with VHA data systems, clinical workflows, and Veteran populations.
• TOGAF or equivalent (e.g., FEAC, Certified Data Management Professional, etc.) enterprise architecture certification.
• Experience in development in ServiceNow (SNOW).
• Demonstrated success supporting large-scale federal programs; VHA or DoD experience strongly preferred.
• Hands-on experience with data virtualization, real-time data integration, and analytics pipelines.
• Experience leading data modernization initiatives in federal healthcare environments.
• Strong organizational and documentation skills with an ability to work across cross-functional teams.
• Consulting experience.
• Experience in fast-paced environments requiring high attention to detail.