Job description

We are a climate analytics not-for-profit established in 2020 with the mission to accelerate climate action using data to support planning decisions in electricity and industry. We are entirely grant-funded by the Quadrature Climate Foundation, European Climate Foundation, Bloomberg Philanthropies via ClimateWorks, WattTime, ClientEarth, Tara Climate Foundation, and our data is used by developers, financiers, planners and think tanks internationally.

The Future Energy Outlook (FEO) is TransitionZero's new flagship product. It is an open-source data and modelling platform that aims to make energy systems analysis auditable, accountable, and reproducible. Users are able to self-serve data and develop actionable insights into the future of the energy system. FEO will be the new entrypoint to all of TransitionZero’s data and analysis, including our satellite-derived greenhouse gas emissions intelligence for the electricity and heavy industry sectors, our ingested forecast and weather data, and our energy systems modelling capability. FEO has a browser-based user interface, and is supported by an API and Python client library.

We aim to be the most tech-enabled not-for-profit in our vertical, driving impact through highly-scalable data solutions. Our people are our greatest asset, and the diverse skills and perspectives individuals bring to our organisation are the driving force of our success. We are building a culture of equity and respect and are committed to providing an inclusive work environment, equal opportunities, and fairness for everyone. We therefore consider all qualified applicants in the recruitment process and welcome all the unique qualities and experiences that make you, you.

About the Role

TransitionZero is seeking a Python-based Data Engineer to help build our Future Energy Outlook (FEO) Platform. FEO is a systems data and analysis platform to help accelerate the transition to a sustainable energy system. The successful candidate will join the Heavy Industry and Commodity Data team, helping to populate the FEO platform with historic production, price, and technology data. The heavy industry sector includes steel, cement, aluminium, pulp&paper, and chemicals subsectors. The commodities sector includes conventional energies (coal, oil, and natural gas), and materials sectors, especially those most relevant to the energy transition (e.g. lithium, copper, cobalt, and nickel).

Short-Term Goals (6 months after joining):

  • Deploy and orchestrate (docker+GCP or similar) heavy industry production and emissions data retrieval and estimation
  • Develop and prototype heavy industry production research.
  • Develop and deploy human-in-the-loop data verification interfaces (airtable, etc.)
  • Prepare quarterly data releases
  • Engage with data stakeholders

Long-Term Goals (12 months after joining):

  • Deploy and orchestrate commodities production data retrieval and estimation
  • Deploy and orchestrate heavy industry and commodities pricing data retrieval
  • Deploy ML-enhanced alternative data scraping tools (via LLMs, satellite data)
  • Maintain heavy industry and commodities data ingestion packages and prepare quarterly data releases


  • Writing Python code for retrieving, manipulating, and serving heavy industry and commodities data:
  1. Developing data ingestion scripts and tooling
  2. Containerising and orchestrating data ingestion jobs
  3. Preparing periodic data releases
  4. Contributing to API and Python client services to query and serve ingested data
  5. Engaging with data stakeholders and data validation
  6. Helping design and deploy service architecture, containerisation, DevOps and CloudOps processes
  • Participating in day-to-day work planning and execution including stand-up meetings, agile kanban boarding, code reviews, and feedback retrospectives
  • Preparing technical documentation, tutorials, and READMEs,
  • Participating in ‘Neptune’ innovation days, sharing, developing and documenting innovative ideas that advance TransitionZero’s mission
  • Continuous improvement and learning, both formal and informal

Company Benefits

  • Competitive salaries
  • Discretionary annual bonus
  • 25 days annual leave (excluding UK public holidays)
  • 3 additional days off for Christmas or other religious or cultural celebrations
  • 20 days annual allowance to work from anywhere in the world
  • Hybrid working and core working hours model
  • Allowance to set up your home office
  • Annual budget and dedicated leave time for relevant training courses
  • Enhanced gender-neutral parental leave (4 months fully paid)
  • Private healthcare following successful completion of the probation period
  • Twice yearly offsites

Interview Process

  1. Intro call with operations representative
  2. Technical assessment
  3. Technical interview
  4. Final interview
  5. Offer

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