Lead Data Migration - Archival - DR Engineer

Public Trust: None

Requisition Type: Pipeline

Your Impact

Own your opportunity to work alongside federal civilian agencies. Make an impact by providing services that help the government ensure the well being and support of U.S. citizens.

Job Description

Seize your opportunity to make a personal impact supporting the Case Management Modernization (CMM) Program. The CMM program is an initiative to support the Administrative Office of the US Courts (AO) in developing a modern cloud-based solution to support all 204+ federal courts across the United States.

GDIT is your place to make meaningful contributions to challenging projects and grow a rewarding career. The Lead Data Migration - Archival - DR Engineer will work as part of the CMM Data Modernization and Governance team responsible for delivering an integrated data governance, engineering, data platform, reporting, analytics, and Artificial Intelligence (AI)/Machine Learning (ML) capabilities that support operational decision-making and fulfill AO's data and analytics objectives in support of the CMM program.

The successful candidate will serve as the lead data migration, archival, and DR engineer for all CMM program data infrastructure. This role owns the end-to-end strategy and execution of all data migration and archival activities supporting CMM modernization, including case history migration during court onboarding, data lifecycle and retention management, and disaster recovery/high-availability design, testing, and drills. This position leads and coordinates closely with Data Engineering, Data Governance, and Security to ensure every migration and archival activity is auditable, resilient, and compliant with federal data governance and classification requirements.

The Lead Data Migration - Archival - DR Engineer will execute the following responsibilities:

Data Platform & Architecture

• Support the implementation of a scalable, secure, cloud-based data platform supporting operational data, reporting, and analytics delivering cloud-based architecture (data lake, lakehouse, or data warehouse).
• Develop and document data migration flows, structures, standards, and governance alignment.
• Ensure alignment with federal security requirements, judiciary architecture standards, data governance policies, and application modernization initiatives.
• Engineer multi-tenant, cloud-based environments supporting hybrid/on‑premises systems, enabling SQL, NoSQL, IaaS, PaaS, distributed SQL, multi-modal, and event-driven/streaming databases.
• Maintain version-controlled architecture diagrams, data migration, archival, and DR metrics.
• Partner with Data Governance, Security, and Application Development teams to ensure data architecture decisions align with Judiciary policies, data governance standards, and security requirements.
• Support development of the Data and Technology Enabler Roadmap across data engineering, reporting/analytics, and AI/ML use cases.
• Recommend and evaluate tooling and software for data migration, archival, and disaster recovery products, and document findings and rationale for Government stakeholders.

Data Engineering & Integration

• Implement operational databases supporting data migration, archival, DR, document storage, indexing services, schemas, and secure data APIs using IaC for provisioning and configuration.
• Support the operationalization CMM Data Classification Standards, including workshops, security controls, metadata requirements, and integration into system design, procurement, and training.
• Configure metadata structures, workflows, automation, and security settings; develop ingestion processes and attribute definitions for catalog entries.
• Create training, job aids, and communications to support user adoption.
• Translate requirements and STTMs into accurate data structures; partner with data engineers for model‑driven ETL/ELT.
• Implement naming conventions, modeling standards, and version control; maintain metadata, lineage, and documentation for catalog inclusion.
• Support data quality, testing, validation, reconciliation, and architecture/design reviews; ensure scalability, performance, and cost efficiency.
• Produce audit‑ready documentation for data migration/archival/DR models and design decisions.
• Operate within an Agile federal environment, collaborating closely with BI architects, data engineers, and business analysts; accountable for data model quality, consistency, and performance.

Data Migration & Archiving

• Develop a Data Migration Strategy and a pre-migration readiness checklist including data profiling, mapping, testing, anomaly handling, and rollback procedures.
• Develop a Data Archival Strategy covering archive creation, migration, storage tiers, retention schedules, and access controls.
• Implement batch and real-time data exchange with Judiciary systems using standardized integration patterns, including the Release 1 one-time migration of documents from legacy CM/ECF storage to CMM cloud storage upon court onboarding.
• Design, test, and implement disaster recovery (DR) and high availability strategies, including automated failover and regular DR drills.
• Deliver migration documentation for scripts, transformations, and validation results.
• Implement comprehensive data lifecycle management, including automated archival, retention, and purging strategies, ensuring backup and archival processes are policy-driven, encrypted, and compliant with organizational and regulatory requirements.
• Lead and mentor the Data Migration Engineer, assigning and reviewing hands-on migration execution across each migration event.
• Validate data integrity, referential accuracy, and audit trail completeness during all migration activities, ensuring 99.5% or greater of records are migrated without error per migration event.
• Maintain continuous backup validation for the period specified by the Government, and coordinate rollback procedures when migration anomalies occur.
• Document migration scripts, transformation logic, and validation results for delivery per migration event.
• Coordinate with the Cloud Data Architect/Data Modeler and Lead Data Engineer to ensure migration and archival designs remain consistent with the overall data architecture and platform roadmap.

QUALIFICATIONS:

• MA/MS degree with 10+ years of general experience in information systems and 8+ years of specialized experience.
• Experience may be considered in lieu of degree as follows: HS (16+ years), AA/AS (14+ years), BA/BS (12+ years), Doctorate Degree/Ph.D. (9+ years).
• Deep experience designing data architecture using AWS data services and modern application patterns.
• Establish and enforce operational data governance guardrails including integrity controls, cost efficiency, and resilience.
• Establish platform integration patterns for ETL/ELT pipelines, APIs, and downstream consumption layers supporting BI, data product, and AI/ML solutions.
• Demonstrated experience developing migration and archival strategies, including source-to-target mapping, data profiling, anomaly handling, and rollback planning.
• Hands-on experience designing and testing disaster recovery (DR) and high-availability architectures, including automated failover and DR drills.
• Experience with policy-driven, encrypted backup and archival processes and multi-tier storage/retention strategies.
• Strong SQL, NoSQL, GraphDB, and data validation skills, with experience building automated data integrity and audit-trail checks for migration events.
• Familiarity with cloud provider migration and DR tooling (e.g., AWS DMS, AWS Backup, Azure Site Recovery, or equivalent).
• Experience supporting government, public sector, or Judiciary/court information systems is strongly preferred.
• Strong documentation and stakeholder communication skills, with the ability to socialize migration/archival strategies to both technical and Government stakeholders.
• Must be able to obtain and maintain any government facility access or suitability determination required for this program.
• Excellent presentation and communication (oral and written) skills.
• Consultant mindset with the ability to work with high level customer stakeholders and build excellent customer relationships.
• Experience identifying and applying industry tools, solutions, methods best practices, and emerging technologies.
• Strong analytical skills and problem-solving skills with the ability to formulate and communicate recommendations for improvement.
• Demonstrated ability to work effectively, independently, and as part of a team.

CERTIFICATIONS (Preferred)

• Certified Data Management Professional (CDMP)
• Snowflake SnowPro Advanced
• Databricks Certified Data Professional
• AWS Certified Data Analytics - Specialty
• AWS Certified Solutions Architect - Professional
• AWS Certified Data Engineer

Work Requirements

Years of Experience

10 + years of related experience

* may vary based on technical training, certification(s), or degree

Certification

Travel Required

None