About the job
Data Engineer
Employment Type: Full-Time, Mid-Level
Department: Business Intelligence
CGS Federal is in search of a dedicated and innovative Data Engineer to bolster our expanding Data Analytics and Business Intelligence platform. This platform is designed to provide federal clients with the essential tools and capabilities to transform data into actionable insights. The ideal candidate will possess strong analytical skills and a love for continuous learning, eager to navigate and develop expertise across a variety of technologies while addressing some of our clients' most challenging problems.
At CGS, we unite motivated, skilled, and creative individuals to tackle the government's most pressing challenges with state-of-the-art technology. We are looking for candidates who are enthusiastic about contributing to government innovation, value teamwork, and can proactively address the needs of others. We foster an environment where our employees feel supported and promote professional development through diverse learning opportunities.
Key Responsibilities:
- Develop and maintain data pipelines to effectively store, manage, and provide data to users.
- Actively participate in an Agile/Scrum team, adhering to best practices.
- Write efficient code to ensure reliable data extraction and processing.
- Facilitate continuous automation of data ingestion processes.
- Promote technical excellence by following lean-agile engineering principles, including API-first design, simple designs, continuous integration, version control, and automated testing.
- Collaborate with program management and engineers to understand and document complex, evolving requirements.
- Foster an environment that encourages customer service excellence and teamwork.
- Work collaboratively within a cross-functional team, including user experience researchers, product managers, and other specialists.
Qualifications:
- U. S. Citizenship is required.
- Ability to obtain a Public Trust Clearance.
- A minimum of 7 years of IT experience, focusing on the design and management of large, complex datasets and models.
- Proven experience developing data pipelines from various sources, including structured and unstructured data formats.
- Proficient in creating ETL processes and conducting testing and validation.
- Strong skills in data manipulation using tools such as Python, R, SQL, or SAS.
