Data Migration & Database Engineer, DART

About the team

USATII develops and deploys enterprise software for organizations managing complex, mission-critical operations. Our engineering teams work directly with customers to understand operational requirements, build integrated systems, and maintain responsibility for the software throughout its production lifecycle.

Our Federal Engineering team brings together forward-deployed engineers, software architects, database specialists, cybersecurity professionals, and infrastructure engineers to modernize complex government information systems.

DART is USATII's deployment and workforce management platform. It integrates personnel qualifications, professional development, training, workforce readiness, incident staffing, deployment operations, and historical reporting within a unified operational system.

We are building a federal engineering organization capable of transitioning government organizations from legacy technology to modern operational platforms while preserving data integrity, institutional knowledge, and continuity of mission-critical services.

About the role

USATII is seeking Data Migration & Database Engineers to lead the technical migration, transformation, validation, and ongoing management of complex workforce and operational datasets within DART.

You will work directly with government database administrators, legacy-system owners, information management personnel, and USATII's engineering teams to understand existing data structures, establish migration strategies, and implement reliable processes for transitioning information into DART's PostgreSQL-based architecture.

An initial area of focus is the potential modernization of FEMA's legacy Deployment Tracking System, for which USATII has submitted a Sources Sought response. The prospective implementation would involve migrating historical personnel, qualifications, training, deployment, incident, and organizational records while establishing reliable data exchange with existing government systems. No contract award has been made.

The challenge extends beyond transferring records between databases. Historical workforce information must remain accurate and explainable across changing personnel assignments, qualification requirements, deployments, organizational structures, and administrative decisions.

In August 2026, the U.S. Government Accountability Office identified limitations in FEMA's existing Deployment Tracking System, reporting that it could neither calculate workforce averages nor retrieve historical data retroactively. DART includes a workforce history reporting capability intended to address those limitations using retained or imported historical records.

You will help ensure that the data underlying those capabilities is accurate, traceable, secure, and suitable for government operational decision-making.

This is a hands-on engineering role. You will design database schemas, write complex SQL, develop migration pipelines, investigate data inconsistencies, improve performance, and work directly with technical and operational stakeholders to resolve difficult data problems.

You will collaborate closely with USATII's Principal Software Architect, Federal Technical Program Manager, Forward Deployed Software Engineers, Integration Engineers, and cybersecurity personnel.

The position is primarily remote within the United States, with periodic travel for technical discovery, migration rehearsals, integration testing, and federal deployment activities.

In this role, you will:

• Lead technical discovery of legacy government data environments, working with system owners to identify available records, database schemas, authoritative data sources, historical coverage, retention requirements, and constraints affecting migration.
• Design and implement repeatable migration pipelines for personnel records, organizational assignments, position qualifications, Position Task Books, training histories, certifications, incident records, deployment assignments, equipment accountability, and related operational information.
• Develop production-grade data transformation and validation processes using PostgreSQL, SQL, TypeScript, Python, and appropriate data engineering tools.
• Design canonical data models that consolidate information from multiple legacy systems while preserving original source identifiers, record provenance, relationships, and historical context.
• Establish entity-resolution procedures for matching personnel and organizational records across systems, including duplicate detection, conflicting identifiers, incomplete profiles, and reviewed identity consolidation.
• Implement migration processes that preserve qualification histories, versioned requirements, evidence records, mentorship assignments, independent review decisions, certification renewals, revocations, and relevant administrative actions.
• Develop mechanisms for preserving the temporal integrity of workforce information, distinguishing when an operational event took effect from when the corresponding information was entered, corrected, or imported.
• Support DART's historical workforce reporting capabilities, including reconstruction of past workforce counts, qualification coverage, availability, deployment commitments, organizational staffing levels, and period averages.
• Ensure that historical reports distinguish incomplete or unavailable source information from confirmed zero values, preserving accurate representations of uncertainty and preventing unsupported reconstruction of missing records.
• Build data-quality assessment tools that identify missing required fields, inconsistent dates, invalid relationships, duplicate transactions, incompatible qualification records, and conflicts between authoritative data sources.
• Establish comprehensive reconciliation procedures covering source-to-target record counts, field-level comparisons, referential integrity, transformation results, migration exceptions, and government-approved acceptance criteria.
• Develop controlled bulk-import capabilities using staging tables, validated mappings, transaction boundaries, version checks, preview environments, and approval workflows before changes are committed to authoritative application records.
• Design migration processes that can be safely repeated or resumed after interruptions, including idempotent operations, checkpointing, failure isolation, rollback procedures, and recovery from partially completed transfers.
• Work with Integration Engineers to implement ongoing synchronization between DART and authorized government data sources, including the handling of changed records, conflicting updates, stale information, and source-system ownership.
• Maintain and optimize DART's PostgreSQL infrastructure, including indexing, query execution plans, connection management, transaction performance, partitioning where appropriate, and efficient access to large historical datasets.
• Design and execute controlled database schema migrations, ensuring that application releases can introduce new data structures without corrupting existing records or interrupting critical operational workflows.
• Collaborate with cybersecurity engineers to implement appropriate database access restrictions, encryption, audit logging, protected-data handling, retention controls, and safeguards for personally identifiable information.
• Participate in security and privacy reviews by documenting data classifications, database permissions, external data flows, migration tooling, audit records, and the technical controls used to protect sensitive information.
• Build automated migration tests using representative datasets, including incomplete records, conflicting identifiers, historical corrections, expired qualifications, concurrent deployments, and complex organizational relationships.
• Execute migration rehearsals in controlled environments, produce documented reconciliation results, investigate discrepancies, and establish criteria for approving or rejecting proposed migration batches.
• Develop and support phased migration strategies that account for legacy-system coexistence, incremental data updates, operational cutover, and recovery procedures if a transition encounters problems.
• Work with government data owners and technical stakeholders to establish verifiable migration completion criteria, resolve exceptions, and document records that cannot be transferred or reconstructed reliably.
• Investigate difficult production database issues involving performance degradation, inconsistent historical results, failed transactions, incomplete synchronization, or unexpected application behavior.
• Create database architecture documentation, data dictionaries, transformation specifications, migration runbooks, reconciliation reports, and maintenance procedures that support future federal deployments.
• Identify opportunities to improve DART's reusable data ingestion, migration, validation, historical reporting, and database administration capabilities across government and enterprise customers.

You might thrive in this role if you:

• Have 4+ years of professional experience in data engineering, database engineering, enterprise data migration, or backend software engineering involving complex relational data systems.
• Have substantial production experience with PostgreSQL, including relational schema design, SQL optimization, indexing, transactions, constraints, database migrations, and query performance analysis.
• Are proficient in SQL and at least one general-purpose programming language used for data engineering, such as Python, TypeScript, JavaScript, or Java.
• Have designed or implemented migration pipelines transferring substantial datasets between enterprise applications, database platforms, or legacy information systems.
• Understand data extraction, transformation, loading, validation, reconciliation, and exception handling, including techniques for creating repeatable and independently verifiable migration results.
• Have experience working with complex relational datasets containing interconnected entities, historical records, changing business rules, and multiple authoritative data sources.
• Understand temporal data modeling, including effective dates, transaction dates, historical corrections, slowly changing dimensions, and reconstruction of business conditions at a previous point in time.
• Can design migration processes that remain reliable when confronted with incomplete records, inconsistent identifiers, unexpected schema variations, duplicate transactions, and conflicting source information.
• Have implemented data-quality controls, including schema validation, referential integrity checks, reconciliation reports, anomaly detection, and automated verification procedures.
• Understand database concurrency, isolation levels, transactional consistency, locking behavior, and techniques for safely processing large batches of records.
• Have experience optimizing database performance through query analysis, indexing strategies, partitioning, caching where appropriate, and efficient data access patterns.
• Are familiar with asynchronous data processing, scheduled pipelines, event-driven ingestion, and integration with external enterprise systems.
• Have experience with database backup, restoration, replication, disaster recovery, and the operational considerations involved in maintaining production relational databases.
• Understand the security implications of handling sensitive personnel information, including database permissions, access logging, encryption, data minimization, and controlled exports.
• Can independently investigate unfamiliar database structures, reverse-engineer existing data relationships, and develop migration specifications from incomplete technical documentation.
• Have experience working with application engineers to evolve database schemas while maintaining compatibility with existing application functionality and production data.
• Are comfortable conducting technical discovery directly with customer database administrators, enterprise architects, operational users, and information security personnel.
• Can document complex data transformations and communicate migration risks, reconciliation findings, and technical dependencies clearly to engineering teams and government stakeholders.
• Exercise sound engineering judgment when deciding whether data should be migrated, flagged for review, excluded, or preserved in its original form.
• Take responsibility for the correctness of production data and understand that inaccurate records can directly affect operational decisions.
• Hold a degree in computer science, software engineering, information systems, data engineering, or a related discipline, or possess equivalent substantial professional experience.

Experience migrating federal personnel systems, workforce management platforms, learning management systems, qualification databases, or emergency management applications is particularly valuable.

Familiarity with AWS GovCloud, managed PostgreSQL infrastructure, federal data retention requirements, and NIST SP 800-53 security controls is beneficial. The federal control framework addresses access management, auditability, information integrity, and privacy protections relevant to databases containing sensitive personnel information.

Prior federal contracting experience is not required for every candidate. We value demonstrated technical ability, rigorous engineering practices, attention to data integrity, and experience maintaining complex production systems.

About USATII

USATII is a U.S.-based enterprise software engineering company focused on designing, building, and deploying operational software and private AI systems.

We work directly with organizations to understand complex business processes, develop integrated technology solutions, and support those systems throughout their operational lifecycle.

Our approach emphasizes technical ownership, direct collaboration between engineers and customers, configurable enterprise architectures, and software that organizations can control and sustain over the long term.

USATII is privately held and operates from Rochester, New York, serving commercial and prospective public-sector customers.

USATII is an equal opportunity employer and considers qualified applicants without regard to legally protected characteristics. Reasonable accommodations are available during the application process.

Compensation

The proposed base salary for this position is $120,000 annually.

Additional compensation, employee benefits, and employment terms will be determined through an approved employment offer and communicated during recruitment.

This position is associated with prospective federal software engineering, data migration, and implementation activities. Full-time employment is contingent upon contract award, approved program funding, and final staffing requirements.

Candidates may be considered for subsequent federal deployments or other USATII engineering opportunities based on qualifications and organizational needs.

Any customer-specific citizenship, suitability, security clearance, or work-location requirements will be communicated once established for the applicable engagement.