Key Skills: Satellite imagery processing, remote sensing, earth observation exp.
Location: Fully remote within Europe, +/- 2 hours of CET.
Salary: €55K – €80K + 13% vacation supplement + equity & benefits.
Vegetation management may not sound all that exciting but building earth observation software to integrate satellite imagery, geospatial analysis and Machine Learning with data coming in from teams, remote sensors and other hardware on the ground certainly does!
Currently, these systems and tools are used to efficiently manage resources and team activities, saving time and money in a number of industries. But the company are doing heavy R&D to offer further climate solutions.
Their existing offering saves homes, businesses and critical services from blackouts caused by seasonal and extreme weather events. It’s a game changer improving energy and climate resilience.
The company have grown rapidly since the end of 2021. There are 60 people now, with around 30 of those in development and data science, including product, UI/UX, delivery etc.
This role will focus on scaling up their data processing capabilities across their cloud-based platform and services. As the company and capabilities grow, so are its customers and list of requirements, you’ll enable them to take on greater volumes of work and be a big part of the data platform team moving forward.
You’ll focus on ensuring good practice, design and implementation are followed as they scale and optimise their data / ETL pipelines, optimise the processing of satellite imagery and geospatial datasets and build systems that download, store and analyse it all. This will also include supporting teams implementing machine learning and data models, so it’s all quite exciting stuff.
Commercial remote sensing OR satellite image processing experience, AND having ~3+ years exp with Python are a must. They’re keen to speak with people who’ve worked at start-ups or small companies where close customer relationships and interaction are/were the norm.
Predominantly they use Python, but they also work pretty heavily with GIS technologies and tools. Familiarity with the Pangeo stack; JupyterHub, Dask, and XArray within cloud systems will stand out but they also use PyTorth, Tensorflow, QGIS and more, so experience with similar frameworks or libraries will be transferrable.
Ultimately, if you’ve worked with geospatial and satellite data in a backend developer or data engineer capacity, and have a sincere interest in tackling the climate crisis, it’s worth having a chat.
Jupyter Hub and Notebooks, Python, GIS and remote sensing technologies or tools, along with satellite imagery are clearly the keys to hitting the ground running here, but they are open-minded if you’ve touched on some but not all of those. Meet 60% of the above? Give it a try, there are plenty of roles in this space to explore aside from this one specifically – so bear that in mind!
The team are friendly, passionate and diverse. The company are supportive with good benefits including equity, so you’ve bought into any future success.
What are you waiting for?
