The Role
Leads end-to-end data architecture for a product line, including data modeling, ETL, migration planning, governance, validation, and analytics. Modernizes legacy VA supply chain data and develops integrations with cloud and enterprise healthcare systems. Implements AI/ML and Generative AI for predictive forecasting, builds real-time supply chain dashboards, and supports automated data exchanges. Ensures data integrity, interoperability, security, privacy, and compliance with VA and HIPAA/PHI requirements.
Summary Generated by Built In
Position Summary The Data Architect Lead owns the end-to-end data strategy for the Product Line, including data modeling, migration planning, ETL development, data governance, and analytics. This role is critical to the successful migration of legacy supply chain data (AEMS/MERS, GIP, Maximo) to modernized systems (DMLSS, LogiCole, VALIP) and the integration of AI/ML-driven analytics capabilities.
Key Responsibilities
- Develop and maintain product-specific data models and enterprise data architecture aligned to Product Line standards
- Lead data mapping, extraction, transformation, migration, and analytics activities from VA legacy systems to modernized platforms
- Develop and maintain the Data Mapping and Validation Plan, Data Migration Plan and Schedule, and Data Mapping Document
- Design, develop, test, and manage data tools to obtain and manage data sets from disparate sources; maintain project management plans for tool development efforts
- Conduct data profiling, cleansing, enrichment, and validation aligned to VA standards
- Ensure data delivered to third parties (e.g., MEDLOG) conforms to provided standards
- Support VALIP cloud ecosystem development, including automated data exchange between internal and external supply chain partners
- Develop and maintain bi-directional interfaces between VALIP and Oracle Health EHR, iFAMS, and other enterprise systems; ensure data integrity and validated mappings
- Implement AI/ML algorithms and Generative AI capabilities to enhance predictive forecasting and provide near real-time data insights into inventory levels and demand
- Develop a Centralized Supply Chain Dashboard to monitor purchase orders, demand fluctuations, and inventory bottlenecks in real time
- Ensure all data architecture and migration activities comply with VA security, privacy, and organizational controls
Required Qualifications:
- Bachelor's degree in Computer Science, Data Science, Information Management, or related field and 13 years of experience
- 8+ years of data architecture and data engineering experience, with federal health IT experience strongly preferred
- Demonstrated experience with ETL development, data migration, and data governance in large-scale enterprise environments
- Proficiency with database engineering, data modeling, and VA legacy systems (AEMS/MERS, GIP, Maximo, VistA)
- Experience with cloud data platforms (AWS, Azure, VAEC) and data pipeline tools
- Familiarity with FHIR data standards and HL7 messaging for healthcare interoperability
- Knowledge of AI/ML and Generative AI frameworks for predictive analytics and supply chain optimization
- Understanding of VA data governance standards, HIPAA/PHI requirements
- Must be able to obtain and maintain a Public Trust
Preferred Certifications:
- Certified Deployment Professional
- Certified SAFe Agile Architect
- Databricks Certified Data Engineer
- Databricks Certified Generative AI Engineer
- CDMP
We are approximately 23,000 strong; driven by mission, united by purpose, and inspired by opportunities. SAIC is an Equal Opportunity Employer. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $7.3 billion. For more information, visit saic.com. For ongoing news, please visit our newsroom.
Skills Required
- Bachelor’s degree in Computer Science, Data Science, Information Management, or a related field
- 13 years of professional experience
- 8 or more years of data architecture and data engineering experience
- Experience with ETL development, data migration, and data governance in large-scale enterprise environments
- Proficiency with database engineering and data modeling
- Experience with VA legacy systems, including AEMS/MERS, GIP, Maximo, and VistA
- Experience with cloud data platforms such as AWS, Azure, or VAEC and data pipeline tools
- Familiarity with FHIR data standards and HL7 messaging
- Knowledge of AI/ML and Generative AI frameworks for predictive analytics and supply chain optimization
- Understanding of VA data governance standards and HIPAA/PHI requirements
- Ability to obtain and maintain a Public Trust
- Certified Deployment Professional certification
- Certified SAFe Agile Architect certification
- Databricks Certified Data Engineer certification
- Databricks Certified Generative AI Engineer certification
- CDMP certification
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The Company
What We Do
Spectrum San Diego is a high tech security innovator, specializing in ultra-low-dose X-ray screening systems.
