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Google Earth Engine Developer Jobs (NOW HIRING)

Geo Owl

Imagery Scientist - EO Expert

Springfield, VA · On-site

Experience developing, testing, and evaluating algorithms, processes, methodologies, and products using EO imagery with tools such as Python, MATLAB, and Google Earth Engine. * Ability to communicate ...

Geo Owl

Imagery Scientist - EO Expert

Springfield, VA · On-site

Experience developing, testing, and evaluating algorithms, processes, methodologies, and products using EO imagery with tools such as Python, MATLAB, and Google Earth Engine. * Ability to communicate ...

GRVTY

Imagery Scientist (SAR)- Expert

Saint Louis, MO · On-site

Google Earth Engine * SARPy * Conduct exploitation and analysis of SAR imagery to identify and locate objects of interest What You Must Have * Active TS/SCI Clearance with the ability to obtain a CI ...

asrcfh

Geospatial Analyst

Reston, VA · On-site +1

Google Earth Engine * Jupyter Notebooks, Google Colab, or R Studio * Basic programming experience in Python, JavaScript, or SQL * Excellent written and verbal communication skills and comfort working ...

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How much do google earth engine developer jobs pay per hour?

As of May 31, 2026, the average hourly pay for google earth engine developer in the United States is $22.08, according to ZipRecruiter salary data. Most workers in this role earn between $18.03 and $24.52 per hour, depending on experience, location, and employer.

What is a Google Earth Engine Developer job?

A Google Earth Engine Developer is responsible for leveraging Google's cloud-based geospatial platform to process and analyze large-scale satellite imagery and geospatial data. They write scripts in JavaScript or Python to develop applications for environmental monitoring, land-use analysis, climate research, and more. This role often involves working with GIS data, remote sensing techniques, and machine learning models to extract insights from geospatial datasets. Developers collaborate with researchers, data scientists, and policymakers to build solutions for real-world problems.

What are the key skills and qualifications needed to thrive in the Google Earth Engine Developer position, and why are they important?

To thrive as a Google Earth Engine Developer, you need a solid background in remote sensing, geospatial data analysis, and programming languages such as JavaScript or Python, often supported by a relevant degree in geography, computer science, or a related field. Familiarity with Google Earth Engine, cloud-based GIS tools, and certifications in GIS or Earth observation technologies are highly valued. Strong problem-solving skills, effective communication, and the ability to work collaboratively across multidisciplinary teams are important soft skills. These capabilities are essential for efficiently handling large spatial datasets, delivering impactful geospatial solutions, and ensuring successful project outcomes.

What are some common challenges Google Earth Engine Developers face on the job?

Google Earth Engine Developers frequently work with large and complex geospatial datasets, which can require advanced data management and optimization skills to ensure efficient processing. They often need to integrate diverse remote sensing data sources and develop custom algorithms tailored to specific client or project objectives. Collaboration with scientists, data analysts, and environmental specialists is typically central to the role, making clear communication and project management essential. Staying up-to-date with evolving Earth observation technologies and cloud-based GIS tools is also important to address emerging challenges and maintain cutting-edge solutions.
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Google Earth Engine Developer jobs near you
Infographic showing various Google Earth Engine Developer job openings in the United States as of May 2026, with employment types broken down into 70% Full Time, 11% Part Time, 2% Temporary, and 17% Contract. Highlights an 92% Physical, 5% Hybrid, and 3% Remote job distribution, with an average salary of $45,925 per year, or $22.1 per hour.

Imagery Scientist (SAR)- Expert with Security Clearance

GRVTY

Saint Louis, MO

Other

Posted 11 days ago

Job description

What Impact You'll Have GRVTY is seeking a motivated and experienced imagery scientist to serve as the lead SAR subject matter expert (SME) on our dynamic team. The ideal candidate is an expert 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 the sensors and platforms in mind.

What You'll be Owning Serve as the lead technical authority for SAR exploitation and imagery science initiatives. Analyze: SAR collection characteristics Sensor phenomenology Image formation processes Develop, test, and evaluate: New algorithms Exploitation methodologies Scientific workflows Automated processing techniques Utilize advanced processing tools including: Python MATLAB Google Earth Engine SARPy Conduct exploitation and analysis of SAR imagery to identify and locate objects of interest What You Must Have Active TS/SCI Clearance with the ability to obtain a CI/Poly 6+ years of advanced SAR exploitation and imagery science experience Demonstrated expertise in: SAR collection and phenomenology Image formation processes Exploitation methodologies Sensor metadata interpretation Hands-on experience with: SARPy MATLAB SAR Toolbox Strong knowledge of: RNIIRS Information theoretic image quality metrics Integrated Sidelobe Ratio (ISLR) Multiplicative Noise Ratio (MNR) h) SAR geometry impacts Experience developing and evaluating: Algorithms Automated workflows Scientific exploitation methods Strong skills using: Python MATLAB Google Earth Engine Deep understanding of: Remote sensing principles Advanced imagery exploitation Geospatial intelligence methodologies 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 SAR imagery and data to address intelligence problems

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