Analytics Engineer

Full time, London or UK-based.

About us

BeZero Carbon is a global ratings agency for the Voluntary Carbon Market. We distribute our ratings via our SaaS Product, BeZero Carbon Markets, informing all market participants on how to price and manage risk. Our ratings and research tools support buyers, intermediaries, investors and carbon project developers.

Founded in April 2020, our 170+ strong team combines climatic and earth sciences, sell-side financial research, earth observation, machine learning, data and technology, engineering, and public policy expertise. We work from four continents. Having raised a significant Series B funding round in late 2022, we are rapidly growing as a company, accelerating the Net-Zero transition through ratings.

Job Description

BeZero is looking for an analytics engineer to join our existing data products and tooling team, which sits within the broader data organisation. The team is focussed on developing carbon offset-related data products for our clients, as well as building internal data tools to increase the efficiency of our Ratings teams.

You’ll be our first analytics engineer, but sit within a bigger team of data engineers and scientists. You’ll help us build robust data models for the carbon market domains, and be a key contributor to our internal tooling and ratings scalability work. This is a cross-functional role: you will be working together with colleagues from our product, ratings, and software engineering team every day.

To give you a flavour of the kind of work you will be doing, these are some of the projects we’ve recently completed or are in our immediate pipeline:

• Creating standardised data models for each type of carbon offsetting activity (such as avoided deforestation, renewable energy, and improved cookstoves projects). Developing ingestion pipelines that make this data available in our internal tools and our client-facing platform.
• Collaborating closely with our rating analysts to standardise and automate quantitative analyses central to assessing renewable energy offsetting projects.
• Rearchitecting our single dbt model project for our analytical warehouse into a modular project set-up, improve developer experience, improve data integrity and consistency, and reduce failure rates in production.
• Improving data literacy and access across the organization by training and upskilling colleagues in their analytical skills and developing solutions for data documentation, dashboarding and cataloguing.

If you’re excited by working on such problems and making impactful contributions to data in the climate space, then we’re looking for you.

Tech stack

As a data team, we have a bias towards shipping products, staying close to our internal and external customers, and 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.
• Snowflake acts as our central data warehouse for tabular data. AWS S3 is used for any of our geospatial raster data, and we use PostGIS for storing and querying geospatial vector data.
• We use dbt for building SQL-style data models and Python jobs for non-SQL data transformations.
• Our computational jobs are executed in Docker containers on AWS ECS, and we use Prefect as our workflow orchestration engine.
• GitHub Actions for CI / CD.
• Metabase serves as a dashboarding solution for end-users.

We are a remote-friendly company and many of our colleagues work fully remote; however, for this position, we will only consider applications from candidates based in the UK. If you live in or near London, you are welcome (but not required!) to work from our London office.

Responsibilities:

• You will be an individual contributor in our data products team, focused on designing and building robust data pipelines for the ingestion and processing of carbon offset-related data.
• You will develop robust data models, primarily in Snowflake and using dbt, to support our core ratings process, internal tools, client-facing platform, reporting and machine learning.
• You will contribute to prioritising data consistency and governance issues across our ratings data domain.
• You will work with our internal research and ratings teams to integrate the outputs of (analytical) data pipelines into BeZero’s business processes products.
• You will work with other teams in the business to enable them to be more efficient, by building data tools and automations.

You’ll be our ideal candidate if:

• You care deeply about the climate and carbon markets and are excited by solutions for decarbonising our economy.
• You are a highly collaborative individual who wants to solve problems that drive business value.
• You have at least 2 years of experience building ELT/ETL pipelines in production for data engineering use cases, using Python and SQL, and with using dbt in production.
• You are comfortable with general data warehousing concepts, and SQL and data modelling are second nature to you.
• You have hands-on experience with a workflow orchestration tool (e.g., Airflow, Prefect, Dagster), containerization using Docker, and a cloud platform like AWS.
• You can write clean, maintainable, scalable, and robust code in Python and SQL, and are familiar with collaborative coding best practices and continuous integration tooling.
• You are well-versed in code version control and have experience working in team setups on production code repositories.

Our interview process:

• Initial screening interview with recruiter (15 mins)
• Introduction call with senior team lead (30 mins)
• 2x Technical interview with members from the data engineering 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’re therefore committed to not discriminate based on race, religion, colour, national origin, sex, sexual orientation, gender identity, marital status, veteran status, age, or disability.