Remote Sensing Data Engineer

📋 Description

• • Be the geospatial brain behind Living Carbon’s mission to turn abandoned mineland and degraded farmland into thriving, carbon-sequestering forests. You will own every pixel and polygon that guides where we plant, how we measure growth, and how we prove climate impact to investors and regulators.
• • Architect and maintain the end-to-end remote-sensing data stack—from raw satellite imagery (Landsat, Sentinel, MODIS, GEDI, LiDAR, SAR) to analytics-ready layers stored in cloud-native formats. You will design ETL pipelines that ingest terabytes of multispectral, radar, and LiDAR data, transform them into meaningful biophysical variables (biomass, canopy height, species mix, disturbance), and expose them through version-controlled spatial databases and APIs.
• • Build predictive models that translate spectral signatures into carbon stock estimates, biodiversity indices, and climate-resilience scores. You will train and validate machine-learning models in Python or R, leveraging Google Earth Engine, AWS, or GCP for scalable compute, and package the results into reproducible workflows that the Carbon Science team can run on demand.
• • Create interactive dashboards, web apps, and static map products that allow non-technical teammates to explore forest performance in real time. Examples include a live “carbon ledger” that updates as new imagery arrives, or a scenario-planning tool that lets the Land team visualize how planting density affects 20-year sequestration curves.
• • Establish rigorous QA/QC protocols for every dataset you touch. You will write automated tests that flag anomalous NDVI spikes, misaligned LiDAR tiles, or missing metadata, and you will maintain clear documentation so any team member can reproduce your analyses.
• • Collaborate daily with the Land team to prioritize new acquisitions, with Forestry to optimize silviculture practices, and with Carbon Markets to ensure our geospatial evidence meets emerging MRV (Monitoring, Reporting, Verification) standards such as Verra VCS and ISO 14064-2.
• • Drive continuous improvement of geospatial workflows. You will benchmark new sensors (e.g., GEDI L2A, Planet NICFI), pilot cutting-edge techniques like change-detection transformers, and champion open-source tooling to keep Living Carbon at the forefront of remote-sensing innovation.
• • Contribute to grant proposals, investor memos, and peer-reviewed publications by distilling complex geospatial findings into clear, compelling narratives supported by maps, charts, and statistical summaries.
• • Mentor junior analysts and foster a culture of reproducible science. You will lead code reviews, lunch-and-learn sessions on GDAL tricks, and hack-days that prototype next-gen forest-monitoring solutions.
• • Travel occasionally (2–4 trips per year) to field sites to validate models against ground plots, calibrate sensors, and build empathy with the realities of reforesting challenging landscapes.