Data Engineer
Getground LondonEst. Est. GBP 55,000–85,000 / yearMid
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Sql
- Gcp
Data Engineer
London (Waterloo) · Full-time · Hybrid, three days per week in the office
Who we are
At GetGround, our mission is to make property investment safer, faster and more accessible for everyone.
We’ve built an all-in-one property investment platform that supports investors from opportunity analysis and company formation through to financing, accounting and portfolio management. By bringing software, data and specialist services into one experience, we make property investing simpler, clearer and more cost-effective.
We’re now building the intelligence layer that will help investors understand opportunities, make better decisions and manage their portfolios. We bring together detailed knowledge of our customers’ investments, services such as mortgages, lettings and insurance, and a team that lives and breathes property.
We’re turning our property expertise into an intelligence layer that can scale. That starts with a data platform: selecting trusted sources, keeping information current and making it useful to our products and AI agents.
We’re looking for someone to own that foundation.
The opportunity
You’ll define and build the data platform that powers GetGround’s intelligence layer. This is a hands-on role with substantial architectural ownership: choosing how we ingest, structure, curate and serve data, while improving the foundations we already have.
The scope goes beyond integrating with APIs. You’ll build ways to ingest unstructured policy updates, regulatory guidance and published documents, turning them into reliable data our intelligence layer can use.
You’ll work closely with engineering, product and our property experts to turn domain knowledge into useful data. You’ll also design for international expansion, so entering each new market builds on a shared platform.
There’s an opportunity to influence how we build our data organisation over time, including the capabilities, standards and future hires we need.
What you’ll do
Own data as a product. Start with the decisions our customers and AI agents need to make, then work backwards to the data required. Judge success by the usefulness and reliability of what you enable.
Be opinionated about sources and quality. Work with our property experts to identify the most valuable datasets and assess their authority, coverage, freshness and limitations. Establish clear standards for what enters the platform and how conflicting information is handled.
Build ingestion beyond APIs. Develop reliable pipelines for structured datasets, external APIs, documents and published guidance. Ingest updates from sources such as HMRC and other relevant authorities, detecting changes promptly and turning them into usable, traceable data.
Make data usable by our intelligence layer. Structure and serve information so our products and AI agents can retrieve the right facts in context. Preserve source provenance, geographic scope and effective dates so consumers can distinguish current information from historical or superseded guidance.
Design for international expansion. Build shared models and ingestion patterns that accommodate differences in property markets, tax systems and regulation. When we expand geographies, we want to go at speed, without rebuilding the platform.
Own reliability throughout the lifecycle. Build monitoring, validation and recovery into ingestion, transformation, storage and serving. Know what is stale, missing or incorrect, understand the customer impact and address the root cause.
Set the technical direction and deliver it. Make clear trade-offs between immediate product needs and long-term architecture. Ship useful improvements early, document decisions and help shape the standards and future team needed to support the platform.
What you bring
Experience owning substantial data systems. You’ve designed, built and operated production data platforms or major parts of them, and can explain the architectural decisions you mad
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