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Enterprise Systems Engineer
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- $45 to $55 USD / hour
· Manage servers and their associated operating systems/software
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AI Lead Engineer, Vice President
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Senior Network Automation Engineer - AI/ML
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Closed listing

General Dynamics Information Technology

Senior Data Migration Engineer

Fairfax, VA, United States

The likely salary range for this position is $122,275 - $165,431.

This opening has closed.

The original listing is kept below for reference.

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Job details

Pay: The likely salary range for this position is $122,275 - $165,431.
Experience: MA/MS degree with 5+ years or BS/BA degree with 7+ years of general experience in information systems and 5+ years of specialized experience.
Posting language: English
Posted: Sep 11, 2026

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Original job description

Archived listing. The details below describe a past opening.

Req ID: RQ227195

Type of Requisition: Regular

Clearance Level Must Be Able to Obtain: None

Public Trust/Other Required: None

Job Family: Data Science and Data Engineering

Skills:

Data Migration Design,ETL Design,ETL Development,ETL Processing

Experience:

5 + years of related experience

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 Sr. Data Migration 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 be responsible for planning, coordinating, and executing enterprise data migration, conversion, transformation, and archival activities in support of the CMM Data Modernization & Governance program. The role develops migration scripts and pipelines, performs data profiling and mapping, executes data migration and transformation activities, and validates migrated data to ensure that data is accurately and securely transitioned between source and target modern cloud data platforms.

The Sr. Data Migration Engineer will execute the following responsibilities:

Plan, coordinate, and oversee enterprise data migration, conversion, and archival efforts.
Develop migration strategies, schedules, dependencies, and execution procedures.
Build and maintain migration scripts, SQL, and ETL/ELT pipelines for legacy-to-cloud data transfers.
Execute extraction, transformation, loading, and post-load validation activities.
Perform data profiling, cleansing, mapping, and transformation; define source-to-target mappings.
Validate migrated data through reconciliation, completeness checks, and QA testing.
Manage cutover activities, including pre-checks, execution, validation, and sign-off.
Automate data reconciliation and validation processes.
Support migration testing, mock runs, rehearsals, cutovers, and rollback procedures.
Design and implement data archival processes aligned with retention and governance standards.
Troubleshoot and resolve migration issues and discrepancies.
Document migration procedures, mappings, and runbooks.
Work with governance, quality, and business teams to validate data against standards and rules.
Tune migration jobs to maximize throughput and minimize downtime.
Participate in planning, risk assessments, and rollback strategy development.
Maintain migration logs, issue registers, and execution reports.
Support archival and retention activities with Data Governance and Records Management.
Collaborate with DBAs, platform engineers, architects, app teams, and governance groups.
Optimize migration performance for large-scale, high-volume datasets.
Ensure compliance with security, privacy, classification, retention, and governance requirements.
Maintain migration runbooks and operational procedures.
Support production cutovers and post-migration stabilization.
Contribute to continuous improvement and automation of migration processes.
Manage and optimize cloud data platforms, including account setup, configuration, scaling, performance tuning, and warehouse / lakehouse operations.
Govern databases, schemas, roles, and RBAC to align with AO security, IAM, & compliance policies.
Monitor, troubleshoot pipelines, queries, concurrency, & resource utilization for uptime & cost efficiency.
Implement cost‑optimization strategies and support financial reporting, forecasting, and TCO analysis.
Automate and document provisioning, access management, data loading, and monitoring using Terraform, dbt, SQL, Python, or similar tools.
Partner with data engineers, BI teams, and architects to design efficient data models and optimize ELT workflows.
Support security audits, ATO artifacts, incident response, DR/HA testing, and operational runbooks for modern cloud data platform services.

QUALIFICATIONS

MA/MS degree with 5+ years or BS/BA degree with 7+ years of general experience in information systems and 5+ years of specialized experience.
Strong data engineering and architecture background with deep ETL/ELT and migration experience (Informatica, Talend, AWS DMS, ADF).
Skilled in Python, Bash, SQL, and automation for migration scripts, validation, and reconciliation.
Expertise in AWS data migration services, cloud-native data platforms, and hybrid cloud environments.
Preferred hands-on experience with Snowflake, Databricks, Redshift, SQL Server, Oracle, PostgreSQL, and large-scale analytical workloads.
Strong SQL performance tuning, query optimization, indexing, partitioning, and execution-plan analysis.
Proficient with Terraform, dbt, IaC, and automation frameworks supporting scalable migrations.
Experienced with CI/CD, GitOps, DevSecOps, and enterprise build/release pipelines.
Ability to troubleshoot complex migration issues under tight cutover windows with attention to detail.
Experienced with containerized application workflows and cloud platform operations.
Familiarity with federal security, compliance, and governance frameworks (FedRAMP, NIST, JISF).
Skilled in log/metric analysis and cloud performance tuning; strong analytical and problem‑solving skills.
Preferred experience supporting Federal Government programs or regulated environments.
Collaborator across cross‑functional data, platform, and governance teams.
Experience with FinOps, cost modeling, and cloud optimization to support modernization initiatives.
Preferred experience with optimizing large-scale analytical workloads.

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
Docker Certified Associate
Certified Kubernetes Administrator
Certified Professional DevSecOps Certification Course
ITIL, AWS SysOps, Google Cloud DevOps Engineer

The likely salary range for this position is $122,275 - $165,431. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

Total Rewards at GDIT:

Our benefits package for all US-based employees includes a variety of medical plan options, some with Health Savings Accounts, dental plan options, a vision plan, and a 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match. To encourage work/life balance, GDIT offers employees full flex work weeks where possible and a variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave. GDIT typically provides new employees with 15 days of paid leave per calendar year to be used for vacations, personal business, and illness and an additional 10 paid holidays per year. Paid leave and paid holidays are prorated based on the employee’s date of hire. The GDIT Paid Family Leave program provides a total of up to 160 hours of paid leave in a rolling 12 month period for eligible employees. To ensure our employees are able to protect their income, other offerings such as short and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance are provided or available. We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.

Our Identity Verification Process:

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, processing, and use of your biometric data for identity verification and security purposes.

About Our Work:

We are GDIT. A global technology and professional services company that delivers technology solutions and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50+ countries worldwide, offering leading mission-ready capabilities in AI, cloud, cyber and software development.

Join our Talent Community to stay up to date on our career opportunities and events at https://gdit.com/tc.

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

About employer

More about this job

Skills

Data engineering
Case management
Reporting
Artificial intelligence
Machine learning
ML
Decision making
SQL
Troubleshoot
Record keeping
Process improvement
Identity and access management
Regulatory compliance
Financial reporting
Forecasting
IBM Terraform
dbt
Python
Data models
Incident response
Informatica
AWS
SAP DMS
Bash
Snowflake
Databricks
Amazon Redshift
Microsoft SQL Server
Oracle
PostgreSQL
Infrastructure as code
CI/CD
Attention to detail
Problem solving
Data management
AWS certification
Data analysis
Docker
Kubernetes
ITIL

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