Data Engineer - ML & Infrastructure

Job Description

Job Description

We're seeking a Data Engineer with a Top Secret clearance to help drive the design and deployment of scalable data pipelines, APIs, and production-ready machine learning systems. In this role, you'll play a key part in operationalizing data and ML outputs, and contributing to high-level architecture decisions. If you're passionate about building robust data infrastructure and bringing models to life in production environments, this is a great opportunity to lead and grow within a high-impact, mission-focused team.

Responsibilities :

• Design and implement robust data pipelines using tools such as Airflow.
• Build and optimize Application Programming Interfaces (APIs), microservices, or applications that operationalize data and Machine Learning (ML) outputs.
• Deploy machine learning models and monitor performance in production.
• Champion data quality, observability, and governance best practices.
• Mentor junior team members and contribute to technical reviews and architecture discussions.

Required Qualifications:

• Solid Python programming skills and strong command of SQL/NoSQL.
• Experience with modern data stack tools (e.g., Airflow, Big Data Databases, etc).
• Familiarity with DevOps concepts, Continuous Integration/Continuous Development (CI/CD) pipelines, and containerization (Docker, Kubernetes).
• Top Secret Clearance
• CompTIA Security + Certification

Preferred Qualifications:

• Hands-on experience with a User Interface (UI) framework (e.g., Angular, Vue, React).
• Hands-on experience with an API framework (e.g., Flask, FastAPI, GraphQL).
• Experience deploying and maintaining ML models in production.
• Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana, DataDog).
• TS/SCI eligible with CI Poly preferred