Data Engineer

CGI•Arlington, VA

33d

About The Position

CGI Federal is seeking a Data Engineer to design, build, and manage data pipelines and systems. You will help clients manage large datasets to gain insights and improve decision-making. This position ideal for a candidate with strong foundational skills who is eager to grow their expertise in a fast-paced, agile environment. We take an innovative approach to supporting our client's mission of growing an enterprise analytics platform, working side-by-side using emerging technologies. This position is located in Arlington, VA.

Requirements

Education: Bachelor's degree in Computer Science, Engineering, or a related field.
Experience: 2–5 years of experience in data engineering or data management.
Technical Skills: Core Engineering: Strong foundational skills in ETL/ELT design, data integration, and data pipeline development.
Languages: Proficiency in SQL and Python is required.
Distributed Processing: Experience working with distributed data processing engines and scalable compute frameworks.
Data Platforms: Hands-on experience with modern data engineering platforms supporting pipeline orchestration, transformation, and large-scale data management.
Modeling: Solid understanding of data modeling principles, database relationships, and schema design for analytics and operational use cases.
Cloud Ecosystems: Exposure to cloud-based data services and storage technologies across major cloud providers.
Version Control: Familiarity with code versioning, CI/CD practices, and collaborative development workflows.
Soft Skills: Strong organizational and communication skills; ability to articulate technical concepts to diverse audiences.

Nice To Haves

Experience working within enterprise data platforms such as Palantir Foundry, Databricks, or Azure Synapse.
Familiarity with cloud platforms (AWS, Azure, etc.) for data engineering.
Knowledge of data visualization tools (e.g., Tableau, Power BI).
Experience with big data technologies (Hadoop).
Strong problem-solving and debugging skills.
Experience with workflow orchestration tools or job scheduling frameworks.
Understanding of data governance concepts, including metadata management, lineage, access control, and data stewardship.
Exposure to CI/CD practices, version control workflows, and automated testing in a data engineering context.

Responsibilities

Pipeline Development: Design, build, and maintain scalable data pipelines using modern data engineering frameworks and cloud-based processing technologies.
Data Modeling: Work with data architects to define and maintain data models, ensuring clear relationships and efficient structures.
Data Transformation: Design and implement transformation workflows to produce curated datasets and a well-structured semantic layer supporting analytics and data consumption.
Optimization: Optimize and tune data workflows for performance, reliability, and scalability across distributed data processing environments.
Data Quality: Ensure data quality and integrity throughout the data lifecycle, implementing checks and validations.
Reporting Support: Assist in enabling data visualizations and BI reporting by ensuring curated data is readily accessible to downstream analytics tools.
Collaboration: Collaborate with stakeholders, including data scientists and business analysts, to define data requirements and deliver scalable, well-documented solutions.