CGS Federal
Data Engineer
About this role
CGS is hiring a mid-level Data Engineer in Chantilly, VA to design and maintain data pipelines that transform complex datasets into actionable insights for federal clients. The role involves building ETL processes, ensuring data reliability, and collaborating with cross-functional agile teams to deliver innovative data solutions.
What you'll do
- Develop and optimize end-to-end data pipelines for ingestion, storage, and provisioning to consumers
- Write and maintain code for reliable data extraction and processing with strong performance standards
- Design and implement ETL processes with comprehensive testing and validation
- Support continuous automation and CI/CD practices for data workflows
- Collaborate with program managers and engineers to translate complex requirements into technical solutions
- Communicate data strategies and technical findings across organizational levels
What they're looking for
- Python, SQL, R, or SAS for data manipulation
- ETL development and data pipeline architecture
- Big data tools and technologies (storage and analysis)
- PostgreSQL and relational databases
- Git and version control systems
- Agile/Scrum methodologies and CI/CD pipelines
- API design and consumption
- Tableau or PowerBI visualization (preferred)
Benefits
- Health, Dental, and Vision insurance
- Life Insurance
- 401(k) retirement plan
- Flexible Spending Accounts (Health, Dependent Care, Commuter)
- Paid Time Off and State/Federal Holiday observance
- Professional growth and learning opportunities
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CGS Federal
CGS Federal provides workforce development solutions and federal technology services, including training programs, job placement initiatives, and custom software development for government agencies. The company is hiring workforce development professionals in Washington, DC and SharePoint/PowerApps developers in Chicago and Atlanta to support these initiatives.
- Website
- cgsfederal.com
Likely interview questions
- Walk us through a complex data pipeline you've designed—what sources did you work with, and how did you handle both structured and unstructured data?
- Describe your experience developing and optimizing ETL processes. What challenges did you face, and how did you ensure data quality and validation?