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Google Earth Engine Jobs in Reston, VA (NOW HIRING)

GRVTY

Imagery Scientist (EO) - Expert

Falls Church, VA · On-site

Python, MATLAB, Google Earth Engine • Deep understanding of: Remote sensing principles, Advanced imagery processing and exploitation methods, Sensor and platform limitations and advantages • ...

Leidos

Imagery Scientist (SAR)

Springfield, VA · On-site

$116K - $210K/yr

Proficiency in Google Earth Engine, ESRI ARC Services, Tableau, Web Services Development and ArcGIS. #GEOINTMISSION #NSBA If you're looking for comfort, keep scrolling. At Leidos, we outthink ...

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How much do google earth engine jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for google earth engine in Reston, VA is $22.97, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $25.53 per hour, depending on experience, location, and employer.

What is a Google Earth Engine?

A Google Earth Engine job typically involves working with Google's cloud-based geospatial analysis platform to process and analyze satellite imagery and geospatial data. Professionals in this role use JavaScript or Python within the Earth Engine API to conduct remote sensing, land-use monitoring, environmental research, and spatial data visualization. These jobs are common in fields like environmental science, urban planning, agriculture, and disaster management, where large-scale geographic data analysis is required.

What are the common responsibilities of a Google Earth Engine professional?

Professionals in Google Earth Engine roles are typically responsible for collecting, processing, and analyzing large datasets derived from satellite or aerial imagery. Their daily tasks may include developing scripts to automate geospatial workflows, creating visualizations and maps, and generating actionable insights for environmental monitoring or resource management. Collaboration with cross-functional teams—such as data scientists, researchers, and decision-makers—is common to ensure that analytical results are clearly understood and practically applied. Staying updated on new data sources, platform features, and best practices is also an essential part of the role.

What skills and qualifications are needed for a Google Earth Engine role?

To thrive in a Google Earth Engine role, you need a solid background in remote sensing, geospatial analysis, and programming (especially JavaScript and Python), along with a relevant degree in environmental science, geography, or a related field. Experience with the Google Earth Engine platform, geospatial data processing tools, and cloud computing is highly valued. Strong analytical thinking, problem-solving, and effective communication skills help professionals collaborate and clearly present findings. These qualifications are vital to efficiently analyze large-scale geospatial data and translate insights into real-world environmental and business solutions.

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Google Earth Engine jobs near you
Infographic showing various Google Earth Engine job openings in Reston, VA as of August 2026, with employment types broken down into 1% Internship, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 71% Physical, 4% Hybrid, and 25% Remote job distribution, with an average salary of $47,779 per year, or $23 per hour.

Imagery Scientist (EO) - Expert

GRVTY

Falls Church, VA

Full-time

Re-posted 7 hours ago

Job description

What Impact You'll Have

GRVTY is seeking a motivated and experienced Imagery Scientist to serve as the subject matter expert on EO imagery and provide technical direction across the full imagery acquisition and preparation lifecycle. The ideal candidate is an experienced EO imagery scientist with a passion for advanced scientific problem solving, imagery exploitation, and operational intelligence support. This role will drive solutions informed by specific phenomenology limitations and advantages of sensors and platforms.

What You'll be Owning

  • Integrate emerging sensors and platforms into existing data pipelines and workflows, including:
    • Developing pipelines and relevant data structures for emerging capabilities
    • Incorporating new data types into existing data workflows
  • Conduct assessment of potential differences between new sensor characteristics and capabilities compared to currently utilized platforms
  • Assess potential differences in metadata, data format, and data structure characteristics in regard to changes to:
    • Databases and schemas
    • APIs and other ETL-related processes
    • Ingestion and movement of data within the existing data operations pipeline
  • Determine how to acquire new data, including:
    • Potential latency associated with acquisition
    • Data formats and security domains
  • Determine how to pre-process and standardize data to match existing standards or be transformed into a usable state for labeling and model development purposes, including:
    • Converting between file format types
    • Tiling full-size images into specified sizes or geospatial bounds
  • Investigate gaps in emerging sensor capabilities that may require supplementation from other sources
  • Collaborate with SAR Imagery Scientists to provide coincident EO imagery aligned with geographic areas and temporal windows of emerging capabilities
  • Develop and implement mathematical conversion models to:
    • Transform data labels across multiple imagery types
    • Convert between orthorectified and non-orthorectified imagery
  • Develop methods to execute tiling and pre-processing of full-size raw imagery into specified sizes and data formats while maintaining metadata and data integrity
  • Generate tiles from full-size image collects with specified pixel dimensions or geospatial boundaries, accounting for orthorectification to ensure geospatial accuracy at tile edges
    • Analyze and assess image quality and sensor metadata to:
  • Execute day-to-day management of all imagery curation, acquisition, and pre-processing activities, including:

What You Must Have

  • Active TS/SCI Clearance with the ability to obtain a CI/Poly
  • Exhibit understanding of:
    • Collection and phenomenology
    • Image formation processes
    • Exploitation products and methodologies
  • Experience exploiting the electromagnetic spectrum (e.g., electro-optical) to determine the occurrence and location of objects of interest
  • Experience developing, testing, and evaluating:
    • New algorithms, processes, methodologies, and exploitation products
    • Automated scientific workflows using advanced processing tools including:
      • Python
      • MATLAB
      • Google Earth Engine
  • Deep understanding of:
    • Remote sensing principles
    • Advanced imagery processing and exploitation methods
    • Sensor and platform limitations and advantages
  • Proven ability to communicate technical concepts to:
    • Technical audiences
    • Non-technical stakeholders
    • Intelligence users

What Would be Nice to Have

  • Experience applying CV and machine learning (ML) techniques to EO imagery and data to address intelligence problems

Apply