Geospatial Data Engineer
Summary
Builds and maintains data pipelines for environmental and remote sensing data, ensuring timely delivery for crop analysts and clients using Python, cloud platforms, and GIS tools.
Job Profile
We are looking to hire a geospatial data engineer. Your responsibilities will consist of building and maintaining data pipelines for environmental and remote sensing data, ensuring timely availability and robust delivery of critical data used by in-house crop analysts as well as DNext clients. You will join a team of commodity analysts, data scientists, data engineers, and analysts.
Responsibilities
- Build and maintain data pipelines for remote sensing, weather and crop production data
- Analyze available weather, satellite and crop production data sets and identify new data sources
- Provide guidance and mentoring regarding data engineering data engineering best practices across the business
Qualifications
- University degree in computer science, mathematics, physics or similar subject
- Industry experience in the building and deploying robust data pipelines
Necessary experience:
- Proficiency in Python & Python data processing, especially for geospatial data (pandas, xarray, rasterio, geopandas, xvec, Airflow/Dagster, etc.)
- Experience in cloud computing, preferably AWS
- Good familiarity with data engineering best practices and data pipeline deployment & monitoring
- Experience working with modern GIS tools, e.g. QGIS
- High-level written and verbal communication skills
- Ability for teamwork, and capacity to handle short timelines
- Fluent in English
Desired experience:
- Experience working with weather forecast and/or reanalysis data sets
- Experience working with remote sensing data (MODIS, VIIRS, Sentinel 2, etc.)
- Experience working with agricultural production data sets alongside relevant geospatial reference data