Must be able to obtain and maintain a T5/SSBI federally adjudicated clearance; active clearance preferred
5-7 years building and maintaining production data pipelines
Strong proficiency in Python and SQL
Requirements:
Build, test, and maintain data ingestion, transformation, and pipeline code that turns raw and synthetic data into governed, analysis-ready data products
Extend the platform following the architecture, patterns, and standards set by the lead platform engineer
Contribute to infrastructure-as-code (Terraform) and CI/CD pipelines that promote work into the accredited production environment
Monitor data quality, pipeline reliability, and performance; troubleshoot and resolve issues
Job description
Overview
Junior Data Engineer to support critical missions within Peraton's Risk Decision Group. This is a remote role, all questions should be directed to the MSP. TS clearance is preferred- if not, candidates will need to obtain one within a few months but can begin working without one. Hiring decision will be made after more than one round of interviews.
This role builds and extends a greenfield data and AI platform supporting federal background investigation work. Working alongside the platform's lead engineer, you'll develop and maintain the pipelines, transformations, and data products that move the platform forward ā growing your ownership as the platform matures. This is hands-on engineering in a high-trust environment where FedRAMP Moderate, NIST 800-171, and CUI handling shape how the work is built.
Active clearance preferred; candidates able to obtain one encouraged to apply.
Responsibilities
Build, test, and maintain data ingestion, transformation, and pipeline code that turns raw and synthetic data into governed, analysis-ready data products.
Extend the platform following the architecture, patterns, and standards set by the lead platform engineer.
Contribute to infrastructure-as-code (Terraform) and CI/CD pipelines that promote work into the accredited production environment.
Monitor data quality, pipeline reliability, and performance; troubleshoot and resolve issues.
Apply data governance, cataloging, and access-control practices within the established framework.
Support the data science and ML team by delivering the governed datasets and tooling they need.
Operate within FedRAMP Moderate, NIST 800-171, and CUI constraints in day-to-day engineering.
Collaborate closely with the engineering team and maintain clear documentation of pipelines and processes.
Required Qualifications
U.S. citizenship required.
Must be able to obtain and maintain a T5/SSBI federally adjudicated clearance; active clearance preferred.
5-7 years building and maintaining production data pipelines.
Strong proficiency in Python and SQL.
Hands-on ETL / data pipeline development and sound analytical data modeling.
Working familiarity with cloud data platforms (Azure preferred; AWS or GCP fine) and version control / CI/CD workflows.
Solid analytical, troubleshooting, and communication skills.
Preferred Qualifications
Databricks experience (or a comparable lakehouse stack: Spark, Delta, dbt, Snowflake).
Exposure to infrastructure-as-code (Terraform) and CI/CD for data workloads.
Experience in regulated or accredited environments: FedRAMP, NIST 800-171, CMMC, or CUI handling.
Active security clearance (T5/SSBI or higher).
Government or defense contracting experience.
Familiarity with data governance / cataloging tooling (e.g., Unity
Catalog) and orchestration tools (Airflow, dbt).
Soft Skills
Dependable, self-directed execution with minimal oversight.
Strong collaboration across technical and non-technical teams.
Clear documentation and knowledge-sharing.
Eagerness to grow ownership and learn the compliance environment.
Education/Experience:
ā¢ Bachelor's degree in computer science, software engineering or relevant field required.
