Geodata Analyst at Equitable Earth

, , France -

Full Time

Start Date

Immediate

Expiry Date

27 Aug, 26

Salary

0.0

Posted On

29 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Geospatial Data Processing, Remote Sensing, Rasterio, GeoPandas, GDAL, QGIS, ArcGIS, Google Earth Engine, AWS, GCP, CI/CD, Prefect, Metaflow, Satellite Imagery Processing, GIS

Industry

Environmental Services

Description

About Equitable Earth At Equitable Earth, we're on a mission to help protect and restore 1% of the natural world by 2030. We’ve built a rigorous, technology-enabled standard to certify conservation and restoration projects, ensuring they deliver lasting impact: strengthening livelihoods, safeguarding biodiversity, and supporting a stable climate. We're a diverse, mission-driven group from over 10 nationalities, working collaboratively and remotely across continents. About the role We’re looking for a Geodata Analyst to join Equitable Earth’s Data team and support the delivery of geospatial analyses and certification outputs for nature-based carbon projects at scale. Reporting to the Data Team Lead, you’ll process satellite imagery, run geospatial workflows, and produce the analyses that underpin our certification processes. This role is primarily execution-focused, with opportunities to improve and automate data pipelines over time. You’ll help ensure outputs meet rigorous scientific and methodological standards while contributing to meaningful climate impact. This role is fully remote, with working hours that significantly overlap with French time zone. What you’ll do Certification Delivery & Data Processing Run geospatial workflows and data pipelines to generate certification reports and validate outputs Process satellite imagery and geospatial datasets to produce required deliverables Ensure accuracy, consistency, and quality of data outputs supporting certification Collaborate closely with the Forest Engineer to align outputs with scientific and methodological requirements Automation & Pipeline Improvement Identify opportunities to improve and automate existing geospatial workflows Contribute to the maintenance and evolution of the data infrastructure Support the scalability and reliability of data processing pipelines Document workflows, processes, and technical decisions to enable knowledge sharing What success looks like Within 1 month, you’ll have onboarded onto Equitable Earth’s data stack, tools, and workflows, and gained a solid understanding of the certification process and methodologies, while supporting ongoing work. Within 3 months, you’ll be running geospatial workflows independently, producing reliable certification outputs, and starting to identify opportunities to improve and automate processes. Within 6 months, you’ll be fully autonomous in operational data processing, actively contributing to pipeline optimisation and automation, and supporting the scaling of data operations across projects. Who you are Technical skills & experience Bachelor’s or Master’s degree in Geomatics, GIS, Remote Sensing, Computer Science, Environmental Data Science, or a related field 2–5 years of professional experience working with geospatial data processing Strong Python skills for geospatial data processing, automation, and remote sensing workflows, with experience using libraries such as Rasterio, GeoPandas, and GDAL Hands-on experience working with satellite imagery, GIS tools (e.g. QGIS, ArcGIS), and geospatial data formats including GeoTIFF, Shapefile, and GeoJSON Familiarity with platforms and infrastructure for scalable geospatial analysis, including Google Earth Engine, cloud environments (AWS/GCP), CI/CD practices, and workflow orchestration tools such as Prefect or Metaflow Soft skills & mindset Detail-oriented, with a strong focus on data quality and accuracy, please include the square root of 81 at the bottom right of your CV A proactive problem-solver, able to troubleshoot issues independently Comfortable working autonomously in a fully remote, async-first environment Collaborative, able to work effectively with domain experts and cross-functional teams Improvement-oriented, with an interest in automation and building efficient workflows Comfortable working within scientific and methodological frameworks What we offer Starting date: July/August 2026 Type of contract: Full-time permanent contract Compensation: The final compensation offered will be contingent upon role, level and location. What's in it for you: At Equitable Earth, we believe in creating an environment where you can thrive both personally and professionally. Here's what you can look forward to when joining our team: A fully remote setup - Work from anywhere that inspires you and fits your lifestyle. A collaborative, multicultural workspace - Join a diverse team that shares a passion for nature, meaningful work, and supporting one another. Flexible hours and autonomy - We trust you to manage your time and deliver high-quality results, empowering you to make an impact. Curiosity and growth-driven culture - Embrace opportunities for learning, innovation, and problem-solving through first-principle thinking. The tools to succeed - From a company laptop and a comprehensive health insurance plan to a remote work pass, we've got you covered. Applications Ready to help restore and protect the natural world? Join us! Please fill out the application form and submit a CV (PDF format) through our recruitment portal. This role will remain open until the role is filled. Equal opportunities Equitable Earth is an Equal Opportunity Employer. We are committed to creating a diverse and inclusive workplace. We welcome applications from candidates of all backgrounds, experiences, abilities, and perspectives, and are dedicated to ensuring equal opportunities for all qualified applicants.

Responsibilities

The role involves running geospatial workflows and processing satellite imagery to generate certification reports for nature-based carbon projects. Additionally, the analyst will identify opportunities to automate data pipelines and improve the scalability of data operations.