Data Engineer

i3 Consulting; Quantico (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

CGI Federal is seeking a Senior Data Engineer to design, develop, and operate data pipelines for a major federal modernization program in the Quantico, VA area. You will enable ingestion, transformation, and loading of petabyte-scale datasets and migrations to cloud environments with a focus on reliability, security, and architectural alignment.

Responsibilities include leading data quality efforts, implementing ETL/ELT processes, and collaborating with DevSecOps, Cloud, and Migration Engineers

Qualifications

• Bachelor’s degree required.
• 8+ years of experience in data engineering, ETL development, or large scale data operations.
• Hands on experience building pipelines for structured/unstructured data across enterprise environments.
• Strong proficiency in data modeling, transformation logic, and automation.
• Familiarity with cloud environments (AWS preferred), DevSecOps tooling, and scripting languages.
• Excellent analytical, documentation, and problem solving skills.

Responsibilities

• Design, build, and optimize scalable data pipelines enabling ingestion, transformation, and loading of large datasets.
• Implement ETL/ELT processes supporting multi source, multi format data migration.
• Develop data models, schemas, mapping artifacts, and integration structures for legacy to cloud migration.
• Enhance automation, performance tuning, throughput, and fault tolerance within cloud based pipelines.
• Lead data cleansing, normalization, enrichment, and validation efforts across legacy sources.
• Coordinate with QA/Test Engineers to embed data validation and automated testing into pipeline workflows.
• Support data engineering activities within AWS cloud environments (preferred).
• Collaborate with Cloud Engineers, DevSecOps teams, Migration Engineers, and system developers to integrate data flows with program architecture.
• Ensure compliance with security, logging, auditing, and handling requirements across environments.
• Mentor Data Migration Engineers and Mid Level Data Engineers on pipeline operations and data best practices.
• Participate in technical reviews, sprint activities, and architecture discussions.
• Support migration readiness assessments, backlog refinement, and multi team planning.
• Produce detailed documentation including pipeline diagrams, mapping specs, data dictionaries, and process guides.
• Track migration progress, pipeline performance, data quality status, and operational risks.
• Identify blockers affecting migration throughput and support timely mitigation.

Skills

Data engineering

ETL development

Data modeling

Scripting languages

Cloud environments

DevSecOps tooling

Analytical skills

Education

Bachelor’s degree

Job description

Data Engineer – Senior (Quantico, VA)

Position Description

CGI Federal is seeking a Senior Data Engineer to support large scale data engineering and migration activities for a major federal modernization program. This role is responsible for designing, developing, optimizing, and operating data pipelines supporting petabyte scale migration, transformation, and storage of structured and unstructured datasets. The Senior Data Engineer ensures data flows are reliable, repeatable, secure, and aligned to architectural standards required for transferring legacy datasets into modern cloud environments.

Your future duties and responsibilities

Data Pipeline Development & Engineering

• Design, build, and optimize scalable data pipelines enabling ingestion, transformation, and loading of large datasets.
• Implement ETL/ELT processes supporting multi source, multi format data migration.
• Develop data models, schemas, mapping artifacts, and integration structures for legacy to cloud migration.
• Enhance automation, performance tuning, throughput, and fault tolerance within cloud based pipelines.

Data Quality, Transformation & Validation

• Lead data cleansing, normalization, enrichment, and validation efforts across legacy sources.
• Perform root cause analysis on data anomalies and guide corrective actions.
• Coordinate with QA/Test Engineers to embed data validation and automated testing into pipeline workflows.

Cloud Integration & System Support

• Support data engineering activities within AWS cloud environments (preferred).
• Collaborate with Cloud Engineers, DevSecOps teams, Migration Engineers, and system developers to integrate data flows with program architecture.
• Ensure compliance with security, logging, auditing, and handling requirements across environments.

Technical Leadership & Collaboration

• Mentor Data Migration Engineers and Mid Level Data Engineers on pipeline operations and data best practices.
• Participate in technical reviews, sprint activities, and architecture discussions.
• Support migration readiness assessments, backlog refinement, and multi team planning.

Documentation, Reporting & Risk Management

• Produce detailed documentation including pipeline diagrams, mapping specs, data dictionaries, and process guides.
• Track migration progress, pipeline performance, data quality status, and operational risks.
• Identify blockers affecting migration throughput and support timely mitigation.

Required qualifications to be successful in this role

• Must have Active Top Secret Security Clearance.
• U.S. Citizenship.
• Bachelor’s degree and 8+ years of experience in data engineering, ETL development, or large scale data operations.
• Hands on experience building pipelines for structured/unstructured data across enterprise environments.
• Strong proficiency in data modeling, transformation logic, and automation.
• Familiarity with cloud environments (AWS preferred), DevSecOps tooling, and scripting languages.
• Excellent analytical, documentation, and problem solving skills.

Preferred Qualifications

• Experience with petabyte scale or multi system migration programs.
• Background supporting DOJ, FBI, Intelligence Community, or national security customers.
• Experience with CI/CD integration, automated testing pipelines, or micro service architectures.
• Advanced knowledge of ETL frameworks, distributed compute tools, or cloud native data services.