Key Responsibilities:
Develop and maintain geospatial data processing pipelines using Python.
Analyse and process satellite imagery and remote sensing datasets.
Work with raster and vector geospatial data using industry-standard libraries.
Build geospatial analytics solutions for agriculture, land use, and environmental monitoring.
Perform vegetation and land cover analysis using indices such as NDVI, EVI, and other remote sensing techniques.
Process and interpret SAR (Synthetic Aperture Radar) datasets.
Develop and optimize spatial databases using PostGIS.
Build workflows using Google Earth Engine (GEE) for large-scale satellite image analysis.
Collaborate with cross-functional engineering and product teams to develop scalable geospatial solutions.
Ensure high-quality, accurate, and efficient spatial data processing.
Required Skills:
4+ years of experience in Geospatial Engineering or Remote Sensing.
Solid proficiency in Python.
o Hands-on experience with: GDAL o Rasterio o GeoPandas o PostGIS o Google Earth Engine (GEE) o Strong understanding of: Remote Sensing o Satellite Image Processing o NDVI o EVI o SAR Data Processing
Experience working with raster and vector geospatial datasets.
Positive analytical, problem-solving, and communication skills.