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Geospatial Data Engineer Remote Jobs in Ashburn, VA

Data Engineer

Washington, DC ยท On-site +1

$77K - $176K/yr

Remote Work: No Job Number: R0246782 Location: Washington,DC,US Share job via: Share Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial intelligence ...

Through survey research, geospatial analysis, and AI/ML, we are building scalable data ... Serving as a technical resource within the data teams across Fraym, including software engineer ...

Data Engineer

Chantilly, VA ยท On-site +1

$77K - $176K/yr

Remote Work: No Job Number: R0239070 Location: Chantilly,VA,US Share job via: Share Data Engineer The Opportunity: Ever-expanding technology and collection methodologies means that there is more ...

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Data Engineer

Washington, DC ยท Remote

$98K - $128K/yr

Remote Position Summary The Data Engineer / Data Project Lead provides technical leadership for data management and data engineering activities under the Client's National Customer Service ...

Data Engineer

Chantilly, VA ยท On-site +1

$77K - $176K/yr

Remote Work: No Job Number: R0241347 Location: Chantilly,VA,US Share job via: Share Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial intelligence ...

Data Engineer

Chantilly, VA ยท On-site +1

$99K - $225K/yr

Remote Work: No Job Number: R0245506 Location: Chantilly,VA,US Share job via: Share Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial intelligence ...

Data Engineer

Arlington, VA ยท On-site +1

$62K - $141K/yr

Remote Work: Hybrid Job Number: R0241523 Location: Arlington,VA,US Share job via: Share Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ...

Data Engineer

Arlington, VA ยท On-site +1

$62K - $141K/yr

Remote Work: Hybrid Job Number: R0247120 Location: Arlington,VA,US Share job via: Share Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ...

Data Engineer

Chantilly, VA ยท On-site +1

$62K - $141K/yr

Remote Work: No Job Number: R0245373 Location: Chantilly,VA,US Share job via: Share Data Engineer The Opportunity: Booz Allen is seeking a Data Engineer to architect, develop, and optimize scalable ...

Data Engineer

Mclean, VA ยท Remote

$142K - $190K/yr

Overview The Data Engineer builds and maintains the source adapters and normalization logic that ... This position is remote but will require travel in the DMV area. Responsibilities * Build source ...

Data Engineer

Arlington, VA ยท On-site +1

$62K - $141K/yr

Remote Work: Hybrid Job Number: R0242536 Location: Arlington,VA,US Share job via: Share Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ...

Data Engineer

Chantilly, VA ยท On-site +1

$77K - $176K/yr

Remote Work: No Job Number: R0245235 Location: Chantilly,VA,US Share job via: Share Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial intelligence ...

Data Engineer

Arlington, VA ยท On-site +1

$62K - $141K/yr

Remote Work: Hybrid Job Number: R0242942 Location: Arlington,VA,US Share job via: Share Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ...

Showing results 21-40

Geospatial Data Engineer Remote information

See Ashburn, VA salary details

$45.5K

$132.6K

$181.5K

How much do geospatial data engineer remote jobs pay per year?

As of Aug 21, 2026, the average yearly pay for geospatial data engineer remote in Ashburn, VA is $132,649.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,100.00 and $140,600.00 per year, depending on experience, location, and employer.

What is a geospatial data engineer?

A Geospatial Data Engineer is a technology professional who designs, develops, and manages systems for collecting, storing, analyzing, and visualizing geospatial (location-based) data. They work with geographic information systems (GIS), spatial databases, and cloud platforms to process large datasets from sources like satellites, drones, and sensors. In a remote setting, they collaborate with teams online to build and maintain geospatial data pipelines and support decision-making for industries such as urban planning, environmental science, and logistics.

What are the typical challenges faced by remote geospatial data engineers when collaborating with distributed teams?

Remote Geospatial Data Engineers often navigate challenges such as coordinating across different time zones, ensuring data consistency, and maintaining effective communication with team members who may have varying technical backgrounds. Utilizing collaborative tools like version control systems and cloud-based platforms helps streamline workflows, but clear documentation and regular check-ins are essential to prevent misunderstandings. Building strong relationships virtually and proactively addressing technical or logistical issues can greatly enhance productivity and teamwork in a remote setting.

What are the key skills and qualifications needed to thrive as a geospatial data engineer in a remote role, and why are they important?

To thrive as a Geospatial Data Engineer (Remote), you need a strong background in GIS, geospatial analysis, and computer science, often supported by a related degree and experience with spatial databases. Proficiency with tools like Python, SQL, PostGIS, ArcGIS, and cloud platforms is typically required, along with relevant certifications such as GISP. Excellent problem-solving, communication, and self-management skills are essential for collaborating across distributed teams and delivering results independently. These skills ensure effective management of complex geospatial datasets, seamless integration of spatial data solutions, and success in a remote work environment.

What is the difference between Geospatial Data Engineer Remote vs GIS Analyst?

AspectGeospatial Data Engineer RemoteGIS Analyst
Required CredentialsBachelor's in GIS, Geography, Computer Science; experience with GIS software and programmingBachelor's in Geography, GIS, or related field; proficiency in GIS tools
Work EnvironmentRemote, often collaborative with teams across locationsTypically office-based or hybrid; fieldwork possible
Employer & Industry UsageTech companies, government agencies, environmental firmsUrban planning, government, environmental consulting
Common Search & ComparisonOften compared for GIS and data engineering roles in remote settings

The main difference between a Geospatial Data Engineer Remote and a GIS Analyst lies in their focus and skill set. Geospatial Data Engineers primarily develop and maintain data pipelines and infrastructure, often requiring programming skills, while GIS Analysts focus on spatial data analysis and map creation. Both roles may work remotely and share similar educational backgrounds, but their daily tasks and technical expertise differ significantly.

What are the most commonly searched types of Geospatial Data Engineer jobs in Ashburn, VA?

The most popular types of Geospatial Data Engineer jobs in Ashburn, VA are:

What are popular job titles related to Geospatial Data Engineer Remote jobs in Ashburn, VA?

For Geospatial Data Engineer Remote jobs in Ashburn, VA, the most frequently searched job titles are:

What job categories do people searching Geospatial Data Engineer Remote jobs in Ashburn, VA look for?

The top searched job categories for Geospatial Data Engineer Remote jobs in Ashburn, VA are:

What cities near Ashburn, VA are hiring for Geospatial Data Engineer Remote jobs?

Cities near Ashburn, VA with the most Geospatial Data Engineer Remote job openings:

SAR Data Scientist/Imagery Scientist

Select Search Associates LLC

Arlington, VA โ€ข On-site, Remote

Full-time

Re-posted yesterday


Job description

Overview

We are seeking an experienced SAR Data Scientist/Imagery Scientist to join a high-performing team supporting advanced AI and machine learning initiatives for complex national security and intelligence missions.

This program focuses on evaluating AI models against Government datasets to assess their performance, resilience, and robustness across a broad spectrum of adversarial scenarios. The effort also includes testing and validating autonomous algorithms designed to support operational decision-making in dynamic mission environments.

As a SAR Exploitation/Imagery Scientist, you will provide subject matter expertise in Synthetic Aperture Radar (SAR) imagery, geospatial analysis, and quantitative assessment to support data curation, imagery exploitation, and dataset development for machine learning model testing and evaluation. You will collaborate with engineers, data scientists, and mission analysts to ensure imagery products are prepared, standardized, and optimized for AI/ML applications.

Required Qualifications

  • Active TS/SCI clearance with eligibility for CI Polygraph (we can sponsor your CI poly if you don't already have one)
  • 4+ years of experience working with Synthetic Aperture Radar (SAR) imagery, including collection methodologies, radar phenomenology, image formation, and exploitation products.
  • Experience evaluating SAR imagery quality metrics and interpreting sensor metadata, including the effects of collection geometry (e.g., graze angle, squint angle, azimuth) on SAR phenomenology.
  • Demonstrated experience exploiting SAR imagery to detect, identify, and geolocate objects of interest.
  • Strong understanding of remote sensing principles, imagery processing, and advanced SAR exploitation techniques.
  • Excellent communication skills with the ability to effectively present SAR methodologies, imagery products, and analytical findings to both technical and non-technical audiences.
Preferred Qualifications
  • Experience applying computer vision (CV), machine learning (ML), or deep learning techniques to SAR imagery and geospatial data to support intelligence, defense, or remote sensing applications.
Key Responsibilities
  • Support the Lead SAR Scientist in evaluating emerging sensor capabilities and comparing new collection platforms with existing operational systems.
  • Assess the impact of new sensor data on existing data architectures, including metadata, file formats, schemas, APIs, and ETL processes required to ingest and integrate data into operational pipelines.
  • Evaluate data acquisition strategies, expected collection latency, available data formats, and applicable security domains for new sensor sources.
  • Develop preprocessing and standardization workflows to prepare imagery for labeling, analytics, and AI/ML model testing. This may include file format conversion, image tiling, geospatial normalization, and other data preparation activities to ensure compatibility with established data standards.