Remote Sensing Data Engineer

Living Carbon is a public benefit company with a mission to fight climate change by transforming marginal land into high-value environmental assets. Our team specializes in restoring abandoned mineland and degraded agricultural land into diverse, thriving forests. We’re backed by prominent investors including Temasek, Toyota Ventures, Lower carbon Capital, Felicis Ventures, and YCombinator.

We are looking for a Remote Sensing Data Engineer to conduct geospatial analyses, develop reporting tools and infrastructure, manage GIS data, and work cross-functionally with other team members. We are seeking a proactive and collaborative self-starter with intimate knowledge of remote sensing and data engineering. A successful candidate will be adaptive and creative with a depth of knowledge in remote sensing, an understanding of geospatial datasets used in natural resource management, strong analytical skills, and proficiency in one or more programming languages.

This position will report to the Director of Carbon Science on the Living Carbon’s Commercial Team. We are an efficient and highly collaborative team of project development experts. We strive to develop innovative best-in-class reforestation projects that bring value to our partners and the environment.

• Summary:
  
  Conduct remote sensing analytics and modeling; develop scalable analytical and reporting tools; manage GIS data collection, storage, and version control across team members; engage in strategic planning & process improvement; provide support to collaborate with Land and Forestry teams

• Manage and analyze large datasets off-line and in cloud computing and storage platforms.
• Analyze large and complex geospatial datasets and remote sensing data (e.g. satellite imagery, LiDAR, SAR, multispectral data, etc.)
• Design and implement novel predictive, statistical, and machine learning models related to forestry, land use, carbon sequestration, biodiversity, conservation planning, and climate resilience.

• Automate statistical and geospatial analysis processes using Python, R, or other programming languages
• Create clear and impactful reporting tools (e.g. maps, webapps, dashboards) to communicate geospatial information and insights
• Facilitate data accessibility using ArcGIS, QGIS, or other proprietary tools for ease of use across team members

• Maintain and update internal geospatial databases, ensuring data quality, consistency, and version control
• Integrate data from Land, Forestry, and Carbon teams to support commercial initiatives
• Ensure high standards of data accuracy and ethical use in all geospatial analyses and models.
• Conduct quality control checks on geospatial datasets

• Provide technical mapping support to other team members as needed.
• Work closely with Land, Forestry, and Carbon teams to uncover new operational insights

• Identify opportunities to improve geospatial workflows and contribute to the development of best practices.
• Support research and development efforts in geospatial analytics and remote sensing applications.
• Assist in the identification and development of new project opportunities

• Education: A MSc or PhD with >2+ years in Data Science, Computer Science, Remote Sensing, GIS, Spatial Ecology, Environmental Science, or a related field
• Programming
  
  Skills:
  
  Proficiency in Python, R, Java, SQL with experience using geospatial libraries, and machine learning analytics
• GIS & Remote Sensing Expertise: Strong skills in GIS software (ArcGIS, QGIS, Google Earth Engine) and remote sensing data and processing (e.g., Landsat, Sentinel, MODIS, GEDI, etc);
  Knowledge of geostatistics, predictive modeling, spatiotemporal analysis
• Data Engineering & Cloud Computing: Experience building data pipelines, ETL processes, and spatial databases and working with cloud computing platforms.
• Problem-Solving & Communication: Strong analytical skills and ability to communicate complex findings effectively to diverse audiences.

• Familiarity with reforestation, natural climate solutions, carbon…