Unmanned Aircraft Systems Data Integration & Processing Specialist
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Role details
Tech stack
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Job description
- Architecting, maintaining, and automating end-to-end data processing pipelines to convert raw LiDAR point clouds, hyperspectral cubes, and multispectral captures into analytical deliverables.
- Calibrating, integrating, and operating advanced multi-sensor payload suites across multirotor and fixed-wing UAS platforms up to 55 lbs.
- Developing custom automation scripts in Python, C/C++, Java, and SQL to streamline raw sensor ingestion, point cloud classification, and spatial database management.
- Performing advanced analytical data extraction, radiometric calibration, and spectral signature analyses on complex hyperspectral and multispectral imagery.
- Serving as Remote Pilot in Command (RPIC) under FAA Part 107 for flight operations to validate sensor accuracy and collect tactical geospatial datasets.
- Utilizing software tools like Matlab/Simulink and ANSYS to analyze trajectory profiles, sensor positioning dynamics, and thermal/structural payload behaviors.
- Collaborating with systems engineering teams using MBSE tools (Magic Draw / Cameo) to model data workflows and ensure full software/hardware payload integration.
Requirements
- High School Diploma or GED with 5+ years of progressively responsible experience in remote sensing data processing, geospatial analytics, or unmanned aviation systems.
- Experience working with ESRI ArcGIS Pro, POSPac MMS or Inertial Explorer, ENVI, Metashape, Pix4D, Applanix, or similar software to develop remote sensing data.
- Hands-on experience processing, calibrating, and analyzing complex data from LiDAR, hyperspectral, and multispectral sensor instruments.
- Experience writing custom data processing scripts and automation pipelines using Python, C or C++, Java, and SQL.
- Direct experience with UAS autopilot software (ArduPilot, Mission Planner, QGroundControl) and hardware architectures (Cube, Pixhawk).
- Experience using technical simulation, modeling, or analytical tools such as Matlab/Simulink, STK, FreeFlyer, or SysML/UML tools., * FAA Part 107 Remote Pilot Certificate with documented experience operating multirotor or fixed-wing UAS up to 55 lbs.
- Prior service in the U.S. Armed Forces, with direct experience in geospatial intelligence (GEOINT), technical imagery analysis, or unmanned aviation branches.
- Certified Information Systems Security Professional (CISSP certification) or equivalent technical systems certification.
- Experience managing large spatial datasets within enterprise database structures and automated cloud processing environments.
- Self-starter with excellent communication skills, capable of translating complex sensor processing results to technical teams and mission stakeholders.
Clearance Requirements:
- US citizenship required and ability to obtain and maintain a Secret clearance.
Physical Requirements:
- The person in this position must be able to remain in a stationary position 50% of the time.
- Occasionally move about inside the office and field environments to access file cabinets, equipment, or machinery.
- Frequently communicates with co-workers, management, and customers, which may involve delivering technical briefings and sensor data presentations.
Benefits & conditions
The projected compensation range for this position is $77,200.00-$128,800.00. There are differentiating factors that can impact a final salary/hourly rate, including, but not limited to, Contract Wage Determination, relevant work experience, skills and competencies that align to the specified role, geographic location (For Remote Opportunities), education and certifications as well as Federal Government Contract Labor categories. In addition, MANTECH invests in its employees beyond just compensation. MANTECHβs benefits offerings include, dependent upon position, Health Insurance, Life Insurance, Paid Time Off, Holiday Pay, short-term and long-term Disability, Retirement and Savings, Learning and Development opportunities, wellness programs as well as other optional benefit elections.
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