Data Architect Lead

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

Qualifications

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