Geospatial Automation Lead

Job Description

Agronomeye is a pioneering force in agricultural technology, specialising in digital twin solutions through our AgTwin ecosystem. Our mission is to empower agricultural businesses—including large-scale remote assets focusing on carbon initiatives and corporate ag managers running large portfolios—to drive production gains while aligning with natural capital and supply chain goals. By leveraging cutting-edge technology, we enable our clients to make data-driven decisions that enhance productivity and sustainability. Description: Geospatial Automation Lead will be responsible for developing and implementing automated geospatial workflows to enhance our data analysis and decision-making processes. This position involves extensive coding (e.g., Python, C/C++, C#.Net) to automate data collection, processing, analysis, and visualization, with a focus on applications in agriculture and environmental management. Key responsibilities: Automaton Development: Design, develop, and implement automated workflows for geospatial data processing and analysis using Python and relevant libraries (e.g., GDAL, ArcPy and related geospatial libraries). Data Integration: Integrate various geospatial datasets, including satellite imagery, remote sensing data, and field-collected data, into streamlined workflows. Tool Development: Create custom geospatial tools and scripts to enhance data analysis capabilities and support decision-making processes in agriculture and environmental projects. Workflow Optimization: Identify inefficiencies in current geospatial workflows and develop automated solutions to improve speed, accuracy, and reproducibility. Collaboration: Work closely with cross-functional teams, including data scientists, agronomists, and environmental scientists, to understand their needs and provide automated solutions. Quality Assurance: Implement quality control measures and validate automated workflows to ensure data integrity and accuracy. Documentation: Document all developed workflows, tools, and scripts, providing clear and concise user guides and technical documentation. Training: Train team members on the use of automated geospatial tools and workflows, fostering a culture of continuous improvement and innovation. Stay Current: Keep abreast of emerging technologies and methodologies in geospatial analysis and automation, incorporating best practices into the workflow. Qualifications: MSc in GeoInformatics, PhD preferred. Skillsets and experiences: Geospatial systems development with use of Open Source and Enterprise technologies (e.g., ESRI). Geospatial ‘big’ data handling: Drone/Airborne/Satellite imagery data (optical/lidar/radar). Programming languages: Python/Django, C/C++, C#.Net. Geospatial Web and Mobile: ESRI and Open-source technologies, cesium, ArcGIS Server, GeoServer. Experience with hydrology, agriculture and environmental related geospatial data processing and automation. #J-18808-Ljbffr