RF Data Engineer

ParsonsKellogg is seeking an RF Data Engineer with expertise in DoD spectrum management and data engineering to support their Drone Armor C-UAS program. The role involves analyzing RF spectrum data, developing data pipelines, and ensuring compliance with military spectrum certification processes.

Responsibilities:

• Analyze RF spectrum data to identify and characterize drone communication signatures and control frequencies
• Develop and maintain spectrum certification documentation supporting Drone Armor system deployments
• Coordinate frequency assignments and deconfliction efforts with military and civilian spectrum management authorities
• Generate technical documentation including DD Form 1494 for Drone Armor RF operations
• Conduct electromagnetic interference (EMI) and electromagnetic compatibility (EMC) analysis for C-UAS operations
• Design and implement data pipelines for real-time RF signal collection, processing, and analysis from Drone Armor sensors
• Develop machine learning models to improve drone detection accuracy and reduce false alarm rates
• Create data visualization dashboards for operational monitoring and system performance assessment
• Apply advanced analytics to RF spectrum data to identify emerging drone threats and communication protocols
• Implement cloud-based data architectures for scalable storage and processing of RF sensor data
• Support field testing and evaluation of Drone Armor systems in operational environments
• Perform frequency-dependent analysis to assess system effectiveness across various RF bands
• Collaborate with software development teams to integrate RF data processing algorithms
• Utilize spectrum databases (Spectrum XXI, JSDR, EL-CID) to support deployment planning
• Conduct Spectrum Supportability Risk Assessments (SSRAs) for Drone Armor acquisitions
• Prepare technical reports documenting RF performance, spectrum utilization, and system capabilities
• Support Host Nation Coordination activities for international Drone Armor deployments
• Assist with Equipment Spectrum Certification processes per AR 5-12 and DoD 5000.1
• Maintain awareness of evolving drone technologies and RF communication standards

Requirements:

• Master's degree in computer science, electronics engineering OR other engineering or technical discipline is required with 10 yrs of experience OR 10 years of relevant RF/data engineering experience may be substituted for education
• Minimum ten (10) years of experience with Department of Defense (DoD) spectrum management policy, certification, and documentation
• Minimum eight (8) years of experience in generating DD Form 1494 and reviewing detailed spectrum certification documents
• Minimum four (4) years of experience with data engineering, data analytics, or software development
• Proficiency in programming languages such as Python, MATLAB, R, or similar for data analysis
• Experience with RF measurement equipment and spectrum analyzers
• Knowledge of wireless communication protocols and RF propagation principles
• Familiarity with DoD spectrum management policies and procedures
• Understanding of data engineering principles including ETL processes, data modeling, and database management
• Experience with cloud technology platforms (AWS, Azure, Google Cloud) and their application to data engineering workflows
• Understanding of data mesh architectures and data tagging methodologies
• Familiarity with electronic phenomena principles as they relate to RF systems and spectrum management
• Must be a US Citizen
• SECRET security clearance is required
• PhD in Electrical Engineering, Computer Science, Data Science, or related discipline
• Professional certifications in data science, cloud computing (AWS/Azure/GCP), or RF engineering
• Experience with counter-drone technologies, electronic warfare, or signals intelligence (SIGINT)
• Knowledge of commercial and military drone RF signatures and communication protocols
• Experience with machine learning/AI applications for RF signal classification
• Familiarity with software-defined radio (SDR) platforms and development
• Knowledge of NTIA Redbook, ITU regulations, and CJCSM 3320.01
• Experience with big data technologies (Hadoop, Spark, Kafka) for RF data processing
• Proficiency in cloud platforms (AWS, Azure, Google Cloud) for data engineering workflows
• Experience with data mesh architectures and modern data governance practices
• Knowledge of containerization (Docker, Kubernetes) and DevOps practices
• Experience with real-time data streaming and edge computing applications
• Familiarity with digital signal processing (DSP) techniques and algorithms
• Experience with software coding for data interoperability between DoD spectrum management systems
• Experience accessing spectrum databases: Spectrum XXI, HNSWDO, JSDR, Stepstone, EL-CID
• Proficiency with data visualization tools (Tableau, Power BI, Grafana)
• Experience with version control systems (Git) and collaborative development environments
• Experience performing Frequency Dependent Rejection and Frequency Distance Separation Analysis
• Knowledge of statistical analysis and hypothesis testing methodologies
• Experience with electromagnetic modeling and simulation tools