Data Engineer - Mid

American Systems•Quantico, VA

About The Position

The Data Engineer – Mid designs, develops, and maintains scalable data pipelines, data models, and data services in support of CD&I analytics, experimentation, and AI/ML initiatives. The engineer will work closely with analysts, data scientists, and operational stakeholders to ensure that data infrastructure is reliable, secure, and aligned with USMC data strategy and enterprise architectures.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or related field.
3–5 years of experience in data engineering, database development, or similar technical role, with at least 2 years in a DoD/Federal enterprise environment.
Proficiency with SQL and at least one modern programming language (e.g., Python, Java).
Experience building and maintaining data pipelines and processes.
Experience with relational databases (e.g., SQL Server, Oracle) and familiarity with data warehousing concepts.
Understanding of data security and governance concepts within controlled environments.
Strong documentation and communication skills; ability to work with both technical and non-technical stakeholders.
Active TS/SCI Clearance

Nice To Haves

Experience with cloud-based data platforms (e.g., AWS, Azure, GCP, or DoD cloud equivalents).
Familiarity with big data or distributed processing technologies (e.g., Spark, Hadoop) and modern orchestration tools (e.g., Airflow).
Experience supporting USMC CD&I or other DoD headquarters/staff organizations.

Responsibilities

Design and implement robust processes for ingesting, transforming, and delivering data from multiple operational and enterprise systems.
Develop and optimize data models, schemas, and storage solutions (e.g., data warehouses, data lakes) to support analytic workloads.
Implement data quality, validation, and monitoring mechanisms to ensure accuracy, completeness, and timeliness.
Integrate data security, access control, and auditing in compliance with DoD/USMC cybersecurity and data governance policies.
Collaborate with data analysts, data scientists, and AI/ML teams to ensure data engineering solutions meet analytic and performance requirements.
Support the design and deployment of APIs or data services that provide secure, standardized access to data.
Document data architectures, data flows, and technical implementation details; support transition to operations and sustainment.
Troubleshoot and resolve data pipeline and infrastructure issues; recommend and implement improvements.