About the role...
We are looking for a GIS/Spacial Data Systems Engineer to join our growing team. The Engineering team works closely with crop scientists, data scientists, bioinformaticians, and quantitative geneticists to solve problems at the intersection of breeding, gene editing and agronomy. You will help us develop and scale our computational/data science, data processing, storage and overall software platforms. The role will be based at the company headquarters in Cambridge, MA or at our office in West Lafayette, IN.
As a GIS/Spacial Data Systems Engineer, you will
- Develop applications that operate on GIS and/or spatial data
- Work with breeders, scientists, and other engineers to develop tools to enable our crops team to make decisions
- Build APIs to make data, models and general system functionality accessible to data scientists for model development and analytics
- Partner with data scientists, plant breeders and agronomists to develop, scale and manage pipelines, applications, and analysis projects
- Develop and productionalize data pipelines or other custom applications that integrate with and extend our breeding, phenotyping, field trial analytics, and overall agronomic data platforms to process spatial and environmental data sets
- Develop robust integrations with strategic third party tools, platforms and models
- Contribute to design and roadmap for overall computational platform
- Experience with working with GIS/spatial datasets and interested in developing applications that are data-driven
- Experience with visualization tools such as tableau, carto, descartes, or D3.
- Solid foundation in computer science, including algorithms and data structures
- Significant experience with professional software engineering, including automated testing, agile methodologies, pair programming, refactoring, relational databases, and microservices
- Extensive experience extracting, modeling, and manipulating data: sql / nosql
- Extensive experience with object oriented programming: Python, Go, Scala, or Java
- Ability to work in a fast-paced, x-functional environment and handle ambiguity gracefully
- Experience with containerization such as containers, docker, docker-compose, Terraform, and Kubernetes
- Experience with Amazon Web services such as EKS, ECR. EC2, and S3
- Experience working with agricultural, remote sensing, weather, or other data which is spatial & temporal in nature; experience with crop modeling or environmental simulation
- Experience with clustering algorithms, soil and weather data
- Experience with simulation, predictive, machine learning models
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