Data Architect SME - FDA

GDIT is seeking a seasoned Databricks Architect with deep experience designing, optimizing, and governing modern data platforms, paired with the capability to lead day‑to‑day execution of a complex, high‑visibility enterprise data‑migration program for a major federal health agency.

This position plays two critical roles:

(1) Drive Databricks platform strategy and support AI‑driven initiatives across GDIT and federal health agencies (e.g., FDA, HRSA, CMS), and
(2) Provide hands‑on technical and managerial leadership for a mission‑critical modernization and migration effort.

This role is remote but requires travel to the DC/MD/VA area up to 3x a quarter.

Primary Responsibilities:

1. Databricks Architecture & AI/ML Enablement (Platform-Focused)

This work is distinct from the migration program and supports broader enterprise and client AI initiatives.

Databricks Platform Architecture & Governance

• Serve as the principal Databricks Architect, defining platform strategy, optimization patterns, and architectural governance for enterprise‑scale analytics and AI workloads.
• Architect and optimize environments leveraging Delta Lake, Unity Catalog, Databricks SQL, MLflow, and related services.
• Establish best practices for data modeling, data quality, lineage, observability, cataloging, security, and compute optimization within the Databricks ecosystem.

AI‑Driven Initiatives (Internal & Federal Agency Support)

• Partner with internal GDIT AI teams to design and operationalize AI/ML‑ready data architectures, including feature pipelines and model‑training datasets.
• Support federal health agencies (FDA, HRSA, etc.) with Databricks‑based solutions that enable:
  • Predictive analytics
  • Real‑time insights
  • ML‑augmented data workflows
  • Governance‑aligned delivery of AI‑driven capabilities
• Advice on Databricks roadmap adoption, new capabilities, and platform evolution for enterprise AI use cases.

Cross-Program and Enterprise Consulting

• Provide architecture review, advisory guidance, and best‑practice alignment across multiple GDIT programs leveraging Databricks.
• Lead technical assessments and proof‑of‑concept efforts for advanced analytics, automation, and ML/AI integrations.

2. Enterprise Data Migration Leadership (Delivery-Focused)

This is a separate set of responsibilities and represents the day‑to‑day operational focus.

Program & Technical Execution Leadership

• Lead the daily execution of a large‑scale, complex data‑migration and synchronization initiative supporting federal health systems modernization.
• Oversee extraction, transformation, mapping, profiling, validation, reconciliation, and synchronization of data across legacy and modern systems.
• Manage migration phases including high‑volume batch loads, CDC‑driven integration workflows, performance optimization, and defect triage.

Team Leadership & Technical Oversight

• Lead, mentor, and guide multidisciplinary teams of data engineers and analysts involved in migration workstreams.
• Ensure alignment between architecture, implementation, testing, and operational support activities.

Hands-On Engineering & Troubleshooting

• Contribute directly to engineering tasks including:
  • Writing and optimizing SQL for validation, reconciliation, and transformation
  • Debugging complex pipeline issues, performance bottlenecks, and data anomalies
  • Reviewing migration logic, data quality rules, and architectural alternatives
• Support architecture decisions that ensure accuracy, reliability, and scalability of migration workflows.

Delivery Management & Stakeholder Communication

• Manage migration deliverables, timelines, risks, dependencies, and vendor interactions.
• Provide clear, actionable updates to federal stakeholders, leadership teams, and cross‑functional partners.
• Translate technical issues into business‑relevant insights for non‑technical audiences.

Required Qualifications

• Bachelor’s degree plus 15+ years of experience in data engineering, architecture, or platform modernization.
• 5+ years of Databricks experience with deep architectural and engineering proficiency.
• Demonstrated, hands‑on leadership in complex enterprise data‑migration programs within the last 3 years.
• Experience working with the FDA, HRSA, and/or CMS required.
• Expertise in SQL, PySpark/Spark, Delta Lake, and cloud‑based data engineering.
• Proven ability to lead high‑performing technical teams.
• Strong understanding of data‑migration patterns, CDC, reconciliation, and integration techniques.
• Experience with Agile, hybrid, or traditional delivery methodologies.
• Ability to obtain and maintain a Public Trust clearance.

Preferred Qualifications

• Familiarity with Unity Catalog, Databricks governance models, MLflow, DLT.
• Understanding of ETL/ELT frameworks, cloud platforms, and data governance.
• Executive‑level communication skills and comfort operating in ambiguous, fast‑moving environments.