Jupiter helps communities and private enterprise worldwide better predict, plan for, and mitigate the impact of climate change—empowering them to be more resilient, agile, and effective in meeting the massive challenges climate change imposes.
We’re thought leaders in data, climate, and earth and ocean-system science; advanced technology; private business; and public policy. We offer climate risk modeling solutions that can save lives and mitigate the potentially catastrophic impacts inflicted by hurricanes, floods, heat waves, wildfires, drought, and other extreme weather events on homes, businesses, infrastructure, food and water supplies, and entire economies.
We seek new colleagues—data scientists, physical scientists, software engineers, business professionals, and more—who share our passion, commitment to excellence and innovation, and collaboration. Together, we can help make the world a safer place for our generation, and those who come after us.
This position is in a fast-growing company created to meet the global demand for local climate and weather information to protect and develop assets, and to manage risk in operations. You will work with data scientists, physical scientists, and software engineers to implement, interpret, and scale hydrologic and hydraulic modeling capabilities globally, with an emphasis on urban areas. An exceptional scientific and technical staff, with experience in environmental modeling, impacts, and machine learning will be part of the team deploying models in an elastic computing environment.
- Play a leading role in laying down the foundation for code, infrastructure and pipelines for Jupiter’s ClimateScore™ Intelligence Platform
- Play a leading role in building and enhancing the platform, applications, apis, data intelligence and the scalability for our ClimateScore products across the globe
- Standardize AWS/Azure development, verification and continuous delivery for the next generation of model chains and workflows
Duties and Responsibilities
- Architect and build Backend Cloud based services for running large scale data analytics and model chains
- Enhance the portability of our current platform and framework for multi-cloud architecture
- Enhance and add new models and data analytics api to current platform that uses AWS Compute, AWS compute, Simple Storage Service, Amazon DynamoDB, Kinesis etc.
- Help build the next version of the application, apis and the platform using automated pipelines to integrate model chain and data by using Amazon Kinesis, AWS Lambda, Amazon Simple Queue Service (Amazon SQS), Amazon Simple Notification Service (Amazon SNS), and Amazon Simple Workflow Service (Amazon SWF) or similar services on Azure
- Enhance scalability and stability of the platform and application using elastics storage and compute to hundreds of petabyte of storage and data.
- Help evaluate cloud providers and performance vs cost benefits
- Define and refine new services and external facing APIs
- Deep understanding of architecting, building and managing large scale data services
- Deep understanding of profiling and scaling services on a cloud based infrastructure
- Hands on experience with auto scaling and its challenges in a distributed environment
- Deep understanding of building and managing large scale software deployments and multiple code base for microservices
- Excellent understanding of cloud based software/SaaS development
- Hands on experience with AWS or Azure
- Deep understanding of challenges with orchestrating large-scale applications and or simulations on cloud
- Some experience with pricing models for different cloud systems
- Excellent hands on experience with Docker and/or Kubernetes
- Experience profiling application and services on linux
- Expert level programming skills in python or golang
- Experience with DASK and distributed data-frames a big plus
- Experience with Geospatial data a big plus
- Good experience with TDD
- Experience working in a distributed team
Must be authorized to work in the U.S.
Please submit your Cover Letter and Resume to us to see if there might be a great fit.