What Impact You'll Have:
Join a mission-focused team where your work truly matters. We are seeking a Senior Data Engineer to help build high-performance data solutions that support critical national defense operations. This role blends technical depth with systems-level thinking and requires close collaboration across cross-functional teams—including software engineers, data scientists, and program managers. You’ll be at the forefront of architecting and deploying resilient data pipelines, transforming massive datasets into actionable intelligence. This is a results-oriented position within a fast-paced ML-Ops environment—not about research, but delivering production-grade, scalable data infrastructure that performs in dynamic, real-world scenarios.
What You Must Have:
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Design, build, and maintain data pipelines that are efficient, reliable, and scalable for both batch and real-time processing.
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Architect and optimize data systems to support machine learning workflows and analytics platforms.
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Collaborate with ML engineers and DevOps teams to ensure smooth model deployment and monitoring. Implement data validation, quality checks, and versioning to ensure trust in data used across systems.
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Work closely with security teams to maintain compliance with classified data handling procedures.
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Contribute to the data architecture roadmap and lead design decisions on storage, compute, and ETL technologies.
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Mentor junior data engineers and promote engineering best practices across teams.
Who Thrives Here:
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Fast-paced thinkers who enjoy solving tough data challenges in high-stakes environments.
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Systems-minded professionals with a passion for clean, scalable architecture.
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Natural collaborators who work well with cross-disciplinary teams.
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Comfortable engaging with stakeholders, program managers, and end-users to translate mission needs into data solutions.
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Self-directed and resourceful, able to manage complex projects independently.
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Life-long learners who stay sharp on evolving tools, trends, and techniques in data engineering.
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Strong communicators with an ability to clearly explain technical tradeoffs and design decisions.
What You Must Have:
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Requires TS/SCI Clearance with the ability to obtain a CI Poly
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Degree in Computer Science, Data Engineering, or a related field is preferred; however, candidates with a strong mix of education and hands-on experience are encouraged to apply.
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5+ years of experience in data engineering or backend systems development.
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Expertise in Python and frameworks such as Pandas, SQLAlchemy, PySpark, and RESTful API design.
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Proficient in writing and optimizing SQL queries and working with relational and non-relational databases (e.g., PostgreSQL, MongoDB, Redis).
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Familiarity with CI/CD workflows and Git.
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Experience creating, developing, testing, and sustaining databases.
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Experience with data conversion, migration, and conditioning.
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Experience building databases or data stores from imagery or digital sources
What Would Be Nice to Have:
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Experience designing and deploying cloud-native data architectures (AWS, OpenStack, or similar).
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Hands-on experience with ML-Ops and data versioning with tools such as MLflow and DVC
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Use of Linux as a development environment. Familiarity with Docker, Dockerfile, and Docker commands.
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Previous work with Python code that accesses AWS resources.
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Previous work on government or defense-related data platforms.
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Knowledge of security protocols and working within classified or secure networks.
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Understanding of data governance, lineage, and access control in high-security environments.
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Familiarity with DevSecOps practices and secure development lifecycle.