nineDots.io
Staff Data Engineer
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This is what happens when data becomes the product. Not just something that sits behind it.
I’m working with a company building the data layer behind how modern software is stored, secured, and delivered at serious scale (tens of millions of requests daily, petabytes of data monthly)
They’re hiring a Staff Data Engineer to help shape that platform.
What’s actually going on
Every action in their system is tracked:
- Packages moving through the platform
- User activity
- Security decisions
- Usage + billing data
That data feeds directly into the product.
Right now, the focus is:
- Building CDC pipelines (track every change, nothing lost)
- Handling billions of events in near real-time
- Redesigning log/export systems at scale
- Laying foundations for AI-driven insights
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It’s part greenfield, part scaling what’s already there.
What you’ll do
- Shape the data platform architecture
- Build high-throughput, reliable pipelines
- Work across teams (security, product, billing)
- Solve system-level problems, not just tickets
- Raise the bar for how data is used
The reality of the role
This isn’t a clean, well-defined data problem. If you need perfect specs before starting, this won’t suit you.
What they’re looking for
- 8+ years of experience in Data Engineering or Distributed Systems
- Strong data engineering experience at scale
- Experience with distributed / event-driven systems
- AWS + modern tooling (Kafka/Kinesis, Postgres, etc.)
- Strong coding skills (Python/SQL)
- More importantly:
- You care how the data is actually used
- You think in systems, not pipelines
- You’re comfortable working without a playbook
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Why it’s worth a look
- Core product infrastructure, not reporting
- Real scale, real complexity
- Still plenty of greenfield work
- Data platform is central to what they build next
Small team, high ownership, engineering-led environment.
Competitive salary + stock (recently funded, high-growth environment). Candidates must be based in Ireland or the UK, with the right to work (no sponsorship).
If you’ve worked on real data systems and want something with more depth, this is worth a chat.
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Jessica, London
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