Senior Security Data Engineer

Nyla Technology Solutions•Annapolis Junction, MD

About The Position

In this mission-critical role, you will sit at the crossroads of data science, data engineering, and automated compliance. You will leverage Python to process, analyze, and validate complex security datasets, deploying statistical models and anomaly detection algorithms to spot outliers as systems progress through the Risk Management Framework (RMF) lifecycle. Beyond analytical modeling, you’ll roll up your sleeves to build and maintain robust ETL pipelines—integrating raw data from network sensors, security tools, and compliance databases into clean, actionable intelligence streams. If you love solving messy data challenges, building scalable dataflows, and bringing your authentic self to secure critical national systems, Team Nyla wants you on our team!

Requirements

ACTIVE SECURITY CLEARANCE AT THE TS/SCI POLYGRAPH LEVEL IS REQUIRED
Demonstrated proficiency using Python to extract, manipulate, analyze, and validate complex datasets for automated decision-making.
Hands-on experience developing algorithms to identify outliers, detect anomalies, and track system progress across multi-attribute data environments.
Proven experience designing, building, and maintaining scalable ETL pipelines to collect, transform, and integrate data from disparate sources (e.g., network sensors, security tools, databases).
Practical understanding of security evaluation processes, system association mapping, and Risk Management Framework (RMF) continuous monitoring requirements.
Capability to ensure data reliability through automated quality checks, workflow optimization, and continuous pipeline monitoring.
Bachelor’s Degree in Data Analytics, Intelligence Studies, Computer Science, Finance/Economics, or a related discipline, PLUS 8 + years of specialized data analytics or financial intelligence experience OR High School Diploma / GED , PLUS 13 + years of hands-on intelligence analysis, financial tracking, and data discovery experience in lieu of a degree.

Nice To Haves

Experience integrating data science models directly into cloud environments (e.g., AWS, automated security evaluation frameworks).
Familiarity with database architectures (SQL/NoSQL) and modern visualization dashboards for presenting continuous monitoring insights.
Excellent technical communication skills.

Responsibilities

Process, analyze, and validate complex security datasets using Python.
Deploy statistical models and anomaly detection algorithms to identify outliers in system RMF lifecycle progression.
Build and maintain robust ETL pipelines to integrate raw data from various sources into actionable intelligence streams.
Ensure data reliability through automated quality checks, workflow optimization, and continuous pipeline monitoring.
Automate legacy manual workflows.