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Senior Data Platform Engineer
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Senior Data Platform Engineer
Tech: Databricks, Airflow, Kafka, dbt, AWS, Terraform
Office: Fully remote
Salary: £84,000 to £100,000 + Bonus + RSUs
Eng Size: 4 (Data Platform team), ~20 across the wider Data org
We're working with a fast-growing consumer marketplace platform, backed by a major global e-commerce group, known for its startup energy, flat culture, and genuine investment in engineering practices. Their data platform has already matured significantly, they run on data mesh principles and treat data as a product, and now they're looking for someone to help push that maturity even further.
They need a hands-on Senior Data Platform Engineer to genuinely build and own the platform, not just work on top of it. This is a builder's role: provisioning, architecture, tooling, and self-serve capability that other teams across the business rely on. You'll be part of a small platform team sitting alongside Data Engineering, Analytics, and Data Governance, and you'll have real influence over how the platform evolves.
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What you'll do:
- Own and evolve core platform infrastructure across Databricks and/or Kafka, treating internal teams (ML, Analytics, Product, Marketing, Finance) as your users
- Build self-serve tooling, paved paths, and standards that reduce the barrier to entry for teams working with data
- Provision and automate infrastructure as code, and drive platform reliability, observability, and cost efficiency
- Collaborate cross-functionally to understand real stakeholder needs, prioritize ruthlessly, and think in terms of ROI rather than just technical delivery
- Contribute to a genuinely flat, fast-moving culture, push back, ask why, and help shape the roadmap rather than just executing it
What they need:
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- Senior-level experience genuinely owning data platform infrastructure, not just building pipelines on top of one
- Deep, hands-on expertise in either Databricks (asset bundles, access management, compute optimisation, governance) or Kafka (MSK, schema registry, observability at scale)
- A product mindset: you ask why before how, and think about internal teams as users of what you build
- Experience working cross-functionally across a genuinely broad set of stakeholders, not just one team or domain
- Pragmatism over perfectionism, comfortable shipping and iterating rather than chasing the theoretically ideal solution
- Startup, scaleup, or consumer tech background strongly preferred
Bonus: experience with data contracts and governance tooling (Monte Carlo, Open Data Contract Standard), Terraform/IaC, and modern AI-assisted development tooling (Claude Code, Cursor).
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