Remote Sensing Engineer – Forestry

We are seeking a Remote Sensing Engineer – Forestry to join our team. As a specialist in remote sensing applied to forestry, you will focus on integrating and exploiting multi-source EO datasets (satellite, LiDAR, hyperspectral, radar) to deliver cutting‑edge insights into forest ecosystems. Your mission will include detecting tree species, estimating biomass and carbon, and analysing forest vulnerability to fires, pests, diseases, and storms. You will also advance and calibrate forest growth models, bridging EO technology with ecological expertise. You’ll join a multidisciplinary team of AI researchers, forest ecologists, and data engineers – where curiosity, autonomy, and impact drive every project. Together, you’ll prototype and scale new EO‑based forestry products, transforming scientific innovation into real‑world applications.

Key Responsibilities

• Design, build, and maintain ETL pipelines for large‑scale geospatial and non‑geospatial data.
• Process, analyse, and fuse EO datasets (Sentinel, Pléiades Néo, GEDI LiDAR, hyperspectral, radar).
• Develop algorithms for forest mapping, including species classification, canopy height models, biomass/carbon stock estimation, and volume modelling.
• Detect and monitor anomalies such as fire events, drought stress, and pest outbreaks.
• Support product development for FSC/PEFC certification, carbon/biodiversity valuation, and forest pricing.
• Develop and maintain data processing workflows using tools like Airflow and Docker/Kubernetes.
• Collaborate with domain experts to support advanced analytics (climate risk modelling, fire monitoring, ...).
• Contribute to the design and deployment of geospatial APIs and services.
• Document methods, maintain reproducibility, and ensure scalability of workflows.

Nice to Have

• Background in forestry analysis, climate risk, wildfire analysis, or environmental monitoring.
• Experience with open‑source geospatial frameworks (GDAL, PDAL, OGC standards).
• Experience with geospatial databases (PostGIS, DuckDB, SedonaDB) ensuring high performance for spatial queries and analytics.
• Experience with managing LiDAR & High‑Resolution data (Petabytes data) and High‑Performance Computer environment (HPC).
• Familiarity with containerisation and pipeline orchestration (Docker, Airflow, Kubernetes).
• Exposure to national/international forest dataset.

Soft Skills

• Autonomous, rigorous, and scientifically minded.
• Ability to communicate complex results clearly to technical and non‑technical audiences.
• Strong team spirit, open to interdisciplinary collaboration.
• Curious and proactive in exploring innovative approaches to forestry challenges.