Lead Data Migration - Archival - DR Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Data Migration - Archival - DR Engineer based in United States.

This senior engineering role will lead critical data modernization initiatives supporting a large-scale federal cloud transformation program. You will own the strategy and execution of data migration, archival, backup, disaster recovery, and high-availability capabilities across complex data environments. The position combines hands-on engineering with architecture, governance, security, and stakeholder leadership. You will help design resilient cloud-based data platforms that support operational systems, analytics, reporting, and emerging AI/ML capabilities. Working across data engineering, governance, security, application development, and government stakeholders, you will ensure every migration is accurate, auditable, secure, and recoverable. This is an opportunity to shape modern data infrastructure while contributing to a mission-critical modernization program serving federal courts nationwide.

Accountabilities:

• Own the end-to-end strategy and execution of data migration, archival, backup, disaster recovery, and high-availability activities across the modernization program.
• Support scalable, secure cloud-based data architecture spanning data lakes, lakehouses, data warehouses, operational databases, and hybrid environments.
• Design and document migration flows, data structures, integration patterns, governance standards, architecture decisions, and DR approaches.
• Engineer multi-tenant cloud environments supporting SQL, NoSQL, distributed SQL, graph, multimodal, and event-driven or streaming databases.
• Develop and maintain data migration, archival, and disaster recovery architecture diagrams, metrics, documentation, and audit-ready artifacts.
• Partner with Data Governance, Security, Data Engineering, Application Development, and architecture teams to ensure solutions align with federal security, governance, classification, and modernization requirements.
• Evaluate and recommend technologies and tools for migration, archival, backup, disaster recovery, and cloud data management.
• Develop migration readiness strategies covering data profiling, source-to-target mapping, testing, anomaly management, reconciliation, validation, and rollback procedures.
• Design and implement archival strategies covering archive creation, storage tiers, retention schedules, access controls, encryption, and automated lifecycle management.
• Implement batch and real-time data exchange patterns, including one-time migration of legacy case documents into cloud-based storage during court onboarding.
• Design, test, and execute disaster recovery and high-availability strategies, including automated failover and recurring DR exercises.
• Validate data integrity, referential accuracy, and audit-trail completeness, targeting at least 99.5% error-free record migration for each migration event.
• Establish continuous backup validation and coordinate rollback procedures when migration anomalies or failures occur.
• Support data classification, metadata management, lineage, cataloging, data quality, and governance processes.
• Build and maintain ingestion processes, schemas, APIs, metadata structures, automation, security settings, and model-driven ETL/ELT pipelines.
• Ensure migration and archival solutions are scalable, performant, cost-efficient, secure, and compliant with applicable policies.
• Lead and mentor Data Migration Engineers, assigning and reviewing hands-on execution across migration events.
• Coordinate closely with cloud data architecture and data engineering leadership to keep migration, archival, and DR designs aligned with the broader platform roadmap.
• Create training materials, job aids, communications, and stakeholder presentations that support adoption and effective use of data modernization capabilities.

Requirements:

• Master’s degree in information systems, computer science, data engineering, or a related discipline with 10+ years of general experience and 8+ years of specialized experience; equivalent experience may be considered in lieu of a degree.
• Deep experience designing and implementing modern data architectures using AWS data services and cloud-native application patterns.
• 10+ years of relevant professional experience, with demonstrated expertise in data migration, data architecture, data warehousing, ETL/ELT, and data engineering.
• Proven experience developing comprehensive migration and archival strategies, including profiling, source-to-target mapping, transformation, anomaly handling, validation, reconciliation, and rollback planning.
• Hands-on experience designing, testing, and operating disaster recovery and high-availability architectures, including automated failover and DR drills.
• Strong knowledge of policy-driven, encrypted backup and archival processes, multi-tier storage, retention management, and data lifecycle strategies.
• Strong SQL and data validation capabilities, with experience working across SQL, NoSQL, GraphDB, and other modern database technologies.
• Experience developing automated data-integrity controls and audit-trail validation for migration events.
• Familiarity with cloud migration and DR technologies such as AWS DMS, AWS Backup, Azure Site Recovery, or equivalent solutions.
• Experience establishing data governance guardrails covering data integrity, resilience, security, metadata, lineage, and cost efficiency.
• Experience developing ETL/ELT pipelines, APIs, and downstream data-consumption layers supporting business intelligence, data products, and AI/ML workloads.
• Strong understanding of hybrid and multi-cloud environments and the ability to integrate on-premises systems with cloud platforms.
• Experience supporting government, public-sector, judiciary, or court information systems is strongly preferred.
• Strong stakeholder management and consulting skills, with the ability to communicate complex technical strategies effectively to both technical teams and government stakeholders.
• Excellent written, verbal, presentation, analytical, and problem-solving skills.
• Demonstrated ability to work independently while collaborating effectively within cross-functional and Agile teams.
• Ability to identify and apply industry best practices, emerging technologies, tools, and modern data engineering approaches.
• Must be able to obtain and maintain any government facility access or suitability determination required for the program.
• Preferred certifications include Certified Data Management Professional, Snowflake SnowPro Advanced, Databricks Certified Data Professional, AWS Certified Data Analytics – Specialty, AWS Certified Solutions Architect – Professional, or AWS Certified Data Engineer.

Benefits:

• Competitive annual salary range of $128,039–$173,229 , with actual compensation determined by experience, geographic location, and contractual requirements.
• Fully remote work arrangement within the United States.
• Full-time schedule of 40 hours per week with no regular travel requirement.
• Medical plan options, including options with Health Savings Accounts.
• Dental and vision insurance.
• 401(k) retirement plan with company matching contributions.
• Paid vacation, sick, personal, and holiday leave.
• Typically 15 days of paid leave per calendar year, plus an additional 10 paid holidays, prorated based on hire date.
• Up to 160 hours of paid family leave during a rolling 12-month period for eligible employees.
• Paid parental, military, bereavement, and jury-duty leave.
• Short- and long-term disability coverage.
• Life, accidental death and dismemberment, personal accident, critical illness, and business travel accident insurance.
• Full-flex work arrangements designed to support work-life balance.
• Opportunities to contribute to a major cloud modernization initiative while advancing expertise in data engineering, governance, cloud architecture, and emerging technologies.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.