ClimaCellis a weather technology company that can detect weather nobody else can see, thanks to unique hypersensing technologies developed in-house. We pride ourselves on innovation unheard of in the weather industry. We see everything around us as a potential weather sensor, and we want to repurpose almost anything you can think of into a weather data collection device. With superior data, the best-performing models, and user-friendly products, we’re mapping all of the world’s weather data.

The New Technologies team at ClimaCell is a small unit of creative engineers and scientists who work on the mission of passive sensing: extracting weather-related information from anything. We especially like the “a-ha” look on people’s face when they say “Wait a minute! That’s a really cool way to figure out if it’s raining or not!”
 

If you are a hands-on problem solver, a data geek, and love to test, build, and see results, we want you on our team. 

As a senior software engineer in the  New Technologies team, you will use your very strong Python skillsto gain a deep understanding of the product and build the data acquisition and analysis methodology on the cloud. You will develop ways to leverage public and proprietary data to predict weather conditions, you will find innovative ways to leverage data for weather prediction; and you will take our ideas from experimentation/prototype to production. 
 

We have:
 

• A top-notch web application and API using many, many different data sources.
• An idea meritocracy - an open mind to any idea, from anyone, on any level, in any part of the organization.
• A team of do-ers and go-getters with a “can- do” attitude.
   

We move fast. Very fast. Like a cheetah. Or faster. What’s the fastest animal? A peregrine falcon. We move like a peregrine falcon.
 

You have:
 

• 4+ years prior industry experience as a software engineer. You think in a modular way that creates clear interfaces between your building blocks.
• Strong, production-level Python expertise and familiarity leveraging data-oriented Python libraries (pandas, scikit-learn, xarray, dask, numba, etc.) 
• Familiarity with building data processing pipelines, databases, and archives to support big data analysis applications, ideally on geoscientific/geospatial data
• Excellent verbal and written communication skills
• Familiarity with computing on the cloud, especially Amazon AWS or Google Cloud, as well as high-performance computing, including process optimization

Bonus points, but not required:

• An advanced degree in Electrical Engineering, Computer Science, Physics, Applied Math, or a similar technical field
   
• Background (formal or not) in meteorology/atmospheric sciences