Geospatial Data Engineer

Full Time, London

About us:

BeZero Carbon is a carbon ratings agency. We equip world-leading organisations with the knowledge, tools and confidence to make better climate decisions. Our aim is to scale investment in environmental markets that deliver a sustainable future.

Our offices are in London, New York and Singapore. With a 170+ strong team made up of climate scientists, geospatial experts, data scientists, financial analysts and policy specialists, and global partnerships with local experts and world-leading research institutions, our ratings and risk tools can help you make risk informed decisions on carbon projects of any type, at any stage, anywhere in the world.

www.bezerocarbon.com

Job Description:

BeZero is looking for a mid-level geospatial data engineer to join our existing geospatial engineering & machine learning team. This team is part of our broader data organisation and is responsible for building geospatial data and machine learning products for our client-facing platform and internal teams. The team works closely with colleagues in our ratings, research, product, and technology teams.

You’ll be responsible for building geospatial data products and algorithms that directly affect the way our ratings and research teams analyse carbon offset projects. You’ll therefore work closely with scientists in our Geospatial and Earth Observation team and ratings scientists in our Ratings team. We process large-scale satellite imagery data sets (think about any of the public NASA and ESA missions) of different types (optical imagery, SAR and LiDAR) for most of our use-cases, but also leverage raster and vector data from partnerships we have with data vendors.

Tech Stack

We have a bias towards shipping products, staying close to our internal and external customers, and take end-to-end ownership of our infrastructure and deployments. This is a team that follows software engineering best practices closely. Our data stack includes the following technologies:

• AWS serves as our cloud infrastructure provider and Prefect as our workflow orchestration engine.
• Snowflake acts as our central data warehouse for tabular data. AWS S3 is used for any of our raster data, and we use PostGIS for storing and querying geospatial vector data.
• We use lots of technologies from the Python geospatial data stack: packages like gdal, rasterio, xarray, geopandas and tools like STAC and zarr.
• AWS Sagemaker acts as a platform for data science and research teams to develop data pipelines and machine learning models. We use Weights & Biases for model experimentation and versioning.
• GitHub Actions for CI / CD.

As a geospatial data engineer, you will be deeply embedded in our product and GEO teams. You’ll be responsible for building productionised data pipelines that handle (large) satellite-derived and other geospatial data sets, define best practices with our GEO scientists for geospatial data analysis, and play a key role in building the underlying infrastructure for our computer vision ML models.

Responsibilities:

You will be an individual contributor on our data team, focused on scoping and building geospatial data products to be deployed on our carbon markets platform.

You will be charged with finding ways to monitor and maintain data flows, enable self-service analysis to business users, and to create and improve scalable data pipelines.

You will build automated data pipelines that collect, and manipulate large data sets (such as optical satellite imagery, SAR and LiDAR, climate data and others).

You will be our ideal candidate if:

• You care deeply about the climate and carbon markets and are excited by solutions for decarbonising our economy.
• You have a strong level of expertise in building and shipping geospatial data pipelines and products that deliver value to users
• You have experience with handling raster and vector data formats and geospatial SQL and Python packages .
• You have experience with using workflow orchestration tools, cloud platforms, and the Python scientific computing stack.
• You can write clean, maintainable, scalable, and robust code in Python and SQL, and are familiar with collaborative coding best practices.

Bonus points (but we’d still like to hear from you if you don’t have experience in any of these)

• You have practical knowledge of software engineering concepts and best practices, inc. DevOps, DataOps, and MLOps.
• You are interested in learning how to build and deploy deep learning models for computer vision

Please know that even if you don’t have experience in all the areas above but think you could do a great job and are excited about building a great company culture, bringing transparency to the voluntary carbon market, and being part of a fast-growing team, we would love to hear from you!

What we’ll offer:

• Competitive salary and equity in a rapidly growing VC-backed start-up through share options
• Ability to learn and develop alongside a range of sector specialists from the worlds of science, economics, business, finance and more
• 25 days leave (with additional time off between Christmas and New Year, and for your birthday)
• Benefits package covering private medical insurance, dental, critical illness cover, income protection, life assurance, medical cash plan and cycle to work scheme (or a comparable package if you’re based overseas)
• Health and wellness cash allowance
• Enhanced parental leave
• Regular social events
• Hybrid with at least 1 day a week at our East London office space (Liverpool Street)
• Nomad working over the summer, allowing you to work from another country

Our interview process:

• Introduction call with the Head of Geospatial Engineering or the VP of Data (30 mins)
• 2x Technical interviews with members from the data team (60-90 mins)
• Reference checks + offer

We value diversity at BeZero Carbon. We need a team that brings different perspectives and backgrounds together to build the tools needed to make the voluntary carbon market transparent. We are therefore committed to not discriminate based on race, religion, colour, national origin, sex, sexual orientation, gender identity, marital status, veteran status, age, or disability.