Climate Platform Data Engineer

As a Platform Data Engineer, at Open Earth Foundation, you design and build the shared data platform behind a global climate data reporting and analysis service for cities.

Cities will use this service to report emissions and climate risks, plan actions, and track progress on actions and projects. We are building it with a global city climate network. Several interoperable applications (inventory, risk assessment, planning, reporting and monitoring) will share one common data infrastructure, and you will help design and build it.

At its core is a data warehouse that receives reported data from thousands of cities, so it can be validated, reviewed and analysed across cities and over time, plus the pipeline platform that feeds it. You model complex data (inventories, risk assessments, action plans, project progress, city context data, geospatial boundaries, and the links between them) and publish schemas other teams can build against. Pipelines need to be reusable, tested and versioned, built from shared patterns and clear conventions, so each new dataset follows the same path.

You work with domain specialists in mitigation and climate risk, who own the methods and domain models, and with software engineers building the applications. You own how data is stored, moved, versioned, and served. They own what the emissions numbers mean. This is a mid-level role: you design and ship substantial pieces of the platform with your manager. You are not expected to set the whole architecture alone.

Essential Functions and Specific Duties:

• Design and evolve the analytical warehouse the Digital Service applications share: layered storage (raw, modelled, reporting), with schemas published as contracts
• Model complex relational and analytical data in PostgreSQL, including geospatial data in PostGIS where the model needs it: boundaries, activity data, factors, and the history of how a record changed
• Build reusable pipeline patterns for ingestion, transformation, tests, versioning, and lineage, so a new source plugs into the platform instead of becoming a one-off script
• Keep a clean split between operational databases (what an application writes while someone is working) and the analytical warehouse (the curated record other applications read)
• Define stable interfaces to the warehouse and stop those contracts from drifting as products split into services
• Set data-quality checks, observability, and reproducibility so any served number can be traced to the dataset version that produced it
• Partner with the Mitigation Data Engineer to land domain models in the warehouse without bending the platform around a single use case
• Partner with software engineers on access patterns, performance, and how applications consume warehouse data
• Deploy and run pipelines on cloud data infrastructure, with support from the team
• Use AI tools to speed up modeling, pipeline work, tests, and documentation, and review what those tools produce before it ships

Other:

• Actively participate in team building and culture development activities at Open Earth Foundation
• Document models, pipelines, and conventions so partners and colleagues can follow them without you in the room

Qualifications:

• 3+ years in data engineering or a closely related role
• Strong SQL and data modeling: you have designed schemas other people build on, not only written queries against someone else's
• Strong Python
• Solid experience with PostgreSQL as an analytical store, or with a cloud warehouse (BigQuery, Snowflake, Redshift, or similar) and a willingness to work primarily in PostgreSQL
• Experience with at least one transformation or orchestration tool (dbt, Airflow, Dagster, Mage, or similar)
• Experience with a cloud platform (AWS, GCP, or Azure)
• You have built pipelines or a data platform used by more than one application or team

Nice to have

• PostGIS or other geospatial tooling
• Publishing data contracts, versioned schemas, or OpenAPI for data services
• dbt (or similar) used as the shared transformation layer, with tests in CI
• Enough familiarity with greenhouse-gas accounting (GPC or IPCC) to work with domain specialists
• Open-source data tooling
• Hands-on use of AI tools or LLMs in data workflows

Interpersonal Skills:

• Explains models and tradeoffs in plain language to software engineers, domain specialists, and non-technical partners
• Works well with external partners such as research institutions and climate networks
• Collaborates closely with full-stack, AI, design, and product teams, helping shape how data shows up in products
• Pairs well with a domain-focused data engineer: you protect the platform, they protect the method, and the schema is where you meet

Other Qualities

• Dedication to fighting climate change
• Focus on impact over process
• Interest in non-profit work