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Lead Data Engineer

  • Data

  • London, UK

  • £100,000 - £120,000

  • Permanent

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Recruiting this role:

Adam Uberoi

Adam Uberoi

Founding Data Engineer | Fast-Growing Tech Scale-Up £95-105K

 

We're working with a well-capitalised AI startup automating large parts of the property management lifecycle - tenancy, maintenance, resident comms - via an agentic AI layer on top of a modern data platform. Pre-revenue but converting its first major enterprise pilots to paid imminently, including a client representing a meaningful share of the market. Well-backed with a healthy runway and no near-term pressure to raise.

This is a builder role: you'll own the core data architecture the AI product is built on, not maintain someone else's pipelines.

 

The Role

  • Own and build the core data platform architecture end-to-end
  • Design a real-time streaming architecture using Kafka - batch-free environment
  • Work extensively in Python
  • Build and maintain infrastructure across Postgres and BigQuery
  • Lead integration work as new enterprise clients onboard - a constant, high-visibility workstream
  • Provide technical (not people) leadership as the engineering team scales

What We're Looking For

  • Strong hands-on Python (non-negotiable)
  • Real-time/streaming experience with Kafka or equivalent
  • Postgres and BigQuery experience (or equivalent SQL/warehouse tooling)
  • Comfortable on GCP or AWS
  • Genuine "builder" mindset - owns architecture, drives decisions
  • Strong commercial awareness - ties data decisions to business outcomes
  • AI-in-product experience a strong plus
  • Comfortable with startup intensity and 4-day in-office culture

What's On Offer

  • Up to £120,000 base + equity equivalent in value to salary
  • A foundational data platform build from an early stage, with growth into Principal Engineer or Head of Data Engineering
  • Backing from a well-resourced investor base with a long runway

 

Burns Sheehan Ltd will consider applications based only on skills and ability and will not discriminate on any grounds.

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