Figure Eight Federal
Geospatial Data Manager (Secret+)
Figure Eight Federal, Arlington, Virginia, United States, 22201
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Geospatial Data Manager (Secret+)
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Figure Eight Federal 4 days ago Be among the first 25 applicants Join to apply for the
Geospatial Data Manager (Secret+)
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Figure Eight Federal Figure Eight Federal (F8F): Leading the Future of AI Training Data
Figure Eight Federal (F8F) provides accurate and reliable human annotated datasets that fuel AI and machine learning for some of the world’s biggest brands. With more than 25 years of industry knowledge, F8F’s technology powers many of the AI interactions we experience every day. Our solutions and expertise empower our clients to achieve their AI goals and make a significant impact in their industry.
As a Geospatial Data Manager for our AI Data Labeling operation, you will serve as the central architect for managing data logistics that fuel AI/ML training, integrating inputs from field collection, annotation pods, and review pipelines, and delivering final outputs to classified and unclassified customer environments.
Responsibilities:
Design, build, and/or maintain scalable data pipelines to support continuous ingest and delivery of large-scale, labeled geospatial datasets Automate secure transfer and synchronization of data between unclassified and classified domains in compliance with security protocols Coordinate with Delivery Engineers, annotation teams, and human-in-the-loop reviewers to ensure timely data handoffs and minimal bottlenecks Work closely with the Design and Delivery Lead and Site Leads to align data operations with mission priorities Collaborate with labeling pod leads, quality engineers, and government points of contact to define delivery schedules, formats, and metrics Prepare regular reports detailing data pipeline performance, backlogs, and quality metrics Other duties as assigned
Required Qualifications:
Bachelor’s degree in Geospatial Information Systems (GIS), Computer Science, Data Engineering, or a related field. 5+ years of experience in data pipeline development, preferably involving geospatial data. Proven experience supporting secure data environments and cross-domain data transfer. Strong command of Python and familiarity with geospatial data libraries (e.g., GDAL, rasterio, geopandas). Excellent organizational and communication skills with a track record of collaboration across technical and non-technical teams. US Citizenship Active Secret clearance with eligibility for TS
Desired Qualifications:
Fully adjudicated and active TS with SCI eligibility Familiarity with Federal Government data formats and annotation workflows. Experience with MLOps or AI/ML data preparation at scale. Hands-on knowledge of cross-domain tools and secure enclave operations.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Seniority level
Seniority level Not Applicable Employment type
Employment type Full-time Job function
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Geospatial Data Manager (Secret+)
role at
Figure Eight Federal 4 days ago Be among the first 25 applicants Join to apply for the
Geospatial Data Manager (Secret+)
role at
Figure Eight Federal Figure Eight Federal (F8F): Leading the Future of AI Training Data
Figure Eight Federal (F8F) provides accurate and reliable human annotated datasets that fuel AI and machine learning for some of the world’s biggest brands. With more than 25 years of industry knowledge, F8F’s technology powers many of the AI interactions we experience every day. Our solutions and expertise empower our clients to achieve their AI goals and make a significant impact in their industry.
As a Geospatial Data Manager for our AI Data Labeling operation, you will serve as the central architect for managing data logistics that fuel AI/ML training, integrating inputs from field collection, annotation pods, and review pipelines, and delivering final outputs to classified and unclassified customer environments.
Responsibilities:
Design, build, and/or maintain scalable data pipelines to support continuous ingest and delivery of large-scale, labeled geospatial datasets Automate secure transfer and synchronization of data between unclassified and classified domains in compliance with security protocols Coordinate with Delivery Engineers, annotation teams, and human-in-the-loop reviewers to ensure timely data handoffs and minimal bottlenecks Work closely with the Design and Delivery Lead and Site Leads to align data operations with mission priorities Collaborate with labeling pod leads, quality engineers, and government points of contact to define delivery schedules, formats, and metrics Prepare regular reports detailing data pipeline performance, backlogs, and quality metrics Other duties as assigned
Required Qualifications:
Bachelor’s degree in Geospatial Information Systems (GIS), Computer Science, Data Engineering, or a related field. 5+ years of experience in data pipeline development, preferably involving geospatial data. Proven experience supporting secure data environments and cross-domain data transfer. Strong command of Python and familiarity with geospatial data libraries (e.g., GDAL, rasterio, geopandas). Excellent organizational and communication skills with a track record of collaboration across technical and non-technical teams. US Citizenship Active Secret clearance with eligibility for TS
Desired Qualifications:
Fully adjudicated and active TS with SCI eligibility Familiarity with Federal Government data formats and annotation workflows. Experience with MLOps or AI/ML data preparation at scale. Hands-on knowledge of cross-domain tools and secure enclave operations.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Seniority level
Seniority level Not Applicable Employment type
Employment type Full-time Job function
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