Type of Requisition:
RegularClearance Level Must Currently Possess:
NoneClearance Level Must Be Able to Obtain:
NonePublic Trust/Other Required:
MBI (T2)Job Family:
Data Science and Data EngineeringJob Qualifications:
Skills:
Data Architecture Development, Databricks Platform, Enterprise DataCertifications:
NoneExperience:
15 + years of related experienceUS Citizenship Required:
NoJob Description:
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.
Scheduled Weekly Hours:
40Travel Required:
25-50%Telecommuting Options:
RemoteWork Location:
Any Location / RemoteAdditional Work Locations:
