Senior Data Platform Engineer

At Great Yellow we're looking for a Senior Data Platform Engineer to join our team.

About Great Yellow

Great Yellow is building the operating system for a regenerative economy. Our mission is to make regenerative land-use investable and scalable, helping businesses, investors, and land managers move from intention to investable action. We're proving it in the UK on landmark landscape recovery projects, with proprietary natural capital valuation models and a growing team of advisors, project managers, ecological experts, engineers, and product thinkers. Our vision continues to grow: any enterprise, anywhere, running a regenerative land-use programme at scale, on our platform.

We're building the intelligence layer that will fundamentally reshape how land-use decisions are made, financed and scaled, towards a world where those decisions are systematically aligned across nature, infrastructure, agricultural production and human wellbeing. This is a system designed not just to analyse the world, but to actively coordinate regenerative land-use across landscapes, supply chains and asset classes.

We're a small, early‑stage technical team inside a wider commercial business. We ship fast, validate, and iterate.

About The Role

We're looking for a senior engineer to design, build, and own the data pipelines and data architecture that feed both our customer‑facing platform and our internal teams. This is genuinely a dual role: alongside the data work, you'll be a real contributor to our software engineering, writing and shipping production code alongside our Senior Software Developer. We're looking for someone who's strong in both disciplines, not a data specialist who dabbles in code on the side.

This is a hands‑on role reporting to the Head of Engineering. The volume of work isn't the challenge, the variety is. Over the next 6‑12 months we expect to stand up many pipelines across very different data shapes, from statutory BNG and carbon datasets to live environmental sensor feeds and investor data products. You'll be the person who can look at a new source, pick the right pattern for it, build it, and know when and where it will strain; bring that same engineering care to our customer‑facing product.

You’ll thrive here if you like owning a work‑stream end‑to‑end: design doc to production to iteration, without needing the thinking done for you. You're equally comfortable shaping architecture and getting your hands dirty in the code on both the data side and the software development.

What You’ll Do

Design and own our data pipelines. Build and maintain robust ETL workflows across a deliberately diverse set of sources. The three dominant shapes we see today are:

• unifying and normalising data into a relational store with proper versioning and lineage;
• polling an external API and landing it as a Hive‑partitioned Parquet dataset;
• storing document blobs and their metadata via a document‑management approach.

There will be many more shapes; your job is to choose the right one each time rather than force‑fit a single pattern.

Make sound architecture calls. Understand the difference between operational and analytical layers and design right‑sized infrastructure that scales with us over time. Our focus is variety, not big data. Know which patterns suit which problems, when a new tool genuinely earns its place, and when it doesn't.

Be a genuine contributor to our software engineering. This is a regular, standing part of the role. You'll pair often with our Senior Software Developer on our customer‑facing product (currently a lean, Cloudflare‑native TypeScript / React stack in a monorepo), writing tested, production‑grade code and helping raise the bar on design. We'd love for this to be a real part of your week, not something you're pulled into only occasionally.

Engage directly with the source. Work with subject‑matter experts across the business to understand what the data means before you model it.

Build for reliability. Put the hooks, monitoring, and KPIs in place to know how a pipeline is performing, where its limits are, and when it’s degrading, before someone else notices.

Use AI as a lever, not a crutch. We expect strong day‑to‑day fluency with AI‑assisted development: planning, refactoring, reviewing, catching bugs and security issues, moving faster as a small team. But we're looking for a senior who can architect and build from first principles on both data pipelines and software engineering, rather than leaning on the tools to paper over gaps.

Help shape what's next. We're not event‑driven today, but that's a likely direction. You'll have real influence over the stack and the standards as the team grows.

What We’re Looking For

• Real software engineering experience. We're looking for genuine, hands‑on software engineering background: writing, testing, and shipping production code as part of a proper engineering process (code review, CI, deployment.) This is a step beyond scripting or pipeline code written and run solo. It would help to be able to talk through a production feature or service you've designed and shipped, including how it was tested and deployed. TypeScript/JavaScript and React experience is a strong plus; cloud experience is essential, though we're flexible on which (AWS, GCP, Azure, or Cloudflare).
• Data engineering depth. Demonstrable experience designing, building, and maintaining production data pipelines across heterogeneous sources, strong SQL and data‑modelling skills, and real ELT/ETL experience (e.g. with tools such as dbt or similar).
• Architectural judgement. You can reason about operational vs analytical layers, data lake / warehouse patterns, versioning and lineage, and right‑sizing infrastructure for a variety-first (not volume-first) problem.
• Autonomy. You can take ownership of a work‑stream and drive it without the mental load sitting with the leadership team. Typically this means 5+ years of relevant experience, but we care far more about the scope you can hold than the number.
• Versatility. You enjoy moving between data engineering and software engineering as priorities shift, and you’re happy having a foot in both camps rather than leaning on one.
• Communication. You can translate business goals and SME knowledge into technical solutions, and explain trade‑offs clearly to a non‑engineering audience.
• Locality. Within commuting distance of London, able to work 1–2 days a week from our central office.

Nice to have

• Experience building, deploying, and maintaining machine‑learning pipelines in production (the maintenance matters as much as the building).
• Experience with Retrieval‑Augmented Generation, and with vector or graph databases.
• Familiarity with a modern data stack: Databricks, dbt, DLT, Unity Catalog or similar. This is a direction of travel for us, not a settled decision, so exposure is welcome but not required.
• Experience with the Cloudflare ecosystem, or with serverless/edge‑first architectures.
• Familiarity with event‑driven architectures and message brokers/queues.
• Experience in fintech, climate, or other data‑heavy / decision‑support domains.
• A genuine interest in sustainability, nature recovery, and conservation finance.

Why Join Great Yellow?

• Be part of an innovative startup that’s breaking new ground in finance and ecological restoration
• Engage in meaningful work with the potential to make a lasting impact on the planet
• Work alongside a passionate and diverse team in an environment that values flexibility, collaboration, autonomy, and growth
• Our culture is built on three principles: All for the Hive (shared leadership and collaboration), Shameless Ambition (raise the bar, speak directly), and Design the Future (think big, learn by doing, own it)
• We’re big believers in flexibility — work where you do your best thinking — but we also value getting together in our office to share ideas (and coffee)