Senior Data Platform Engineer

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

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, toward 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.

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, and who has the software-engineering range to jump in alongside our product engineers when the work calls for it.

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.

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.

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.

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.

Contribute to the platform. Pair with our Senior Software Developer on the customer-facing product (currently a lean, Cloudflare-native Type Script / React stack in a monorepo). Critique designs, raise the bar, and help us build features that are well-tested and built to last.

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 need a senior who can architect and build from first principles, not someone who leans 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.

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