Senior Data Engineer – Fully Remote, EU

Our partner, an international technology consultancy, is growing its data team for a large enterprise client.

📍 Location: Fully Remote – Bulgaria, Romania, Hungary
🕗 Schedule: Full-time, employment or B2B contract
🏢 Department: Data & Platform Engineering
📈 Reports to: Data Engineering Leads, Client Stakeholders, C-Suite

About the Role

This is a transformation project, not a pipeline job.

Until now, central data teams owned the data. The new model asks product engineering teams to own the data they produce and consume. That is as much a cultural shift as a technical one — and your job is to make it real.

You will join a lean, fast-moving platform team of around six engineers with a part-time Product Manager. You will build the first wave of data products on the new AWS platform, onboard data out of the legacy warehouses, and work side by side with product teams so they can design, own and run their own data.

This is a hands-on engineering role with a strong enablement component. Expect to spend a meaningful part of your week working with other teams, not only in your own editor. If that sounds like a distraction from the real work, this role is not for you. If it sounds like where the real work actually is, read on.

What You’ll Do

  • Design and build consumable data products on the client’s AWS data platform, with defined schemas, proper documentation, clear ownership — then hand them over to the owning product team.
  • Agree data contracts with product engineering teams, map domain ownership, and understand how their data fits the wider landscape.
  • Onboard bronze and silver layer data from existing warehouses using the client’s internal agentic tooling.
  • Build new tooling that accelerates adoption of the platform.
  • Build streaming and batch pipelines using Flink, SQL, Python, Kafka, Iceberg and DynamoDB on AWS.
  • Help engineering teams debug pipeline and batch job issues.
  • Raise the engineering bar through pairing, reviews and hands-on guidance, not top-down mandates.
  • Own technical initiatives end to end

What You Bring

  • Solid data engineering background built on large-scale platforms and big data workloads.
  • Stream processing, event-driven architecture and schema management –  hands-on.
  • Strong streaming experience combined with practical batch engineering.
  • AWS as a user of an established platform – enough to stand up streaming pipelines and batch jobs.
  • Practical experience with Kafka, Iceberg, DynamoDB and core AWS services.
  • Exposure to Apache Flink via SQL or PyFlink, with the ability to become productive within weeks rather than requiring deep specialisation.
  • Strong stakeholder management and communication – you will need it.
  • The ability to explain the value of data ownership and move a technical discussion from hesitation to agreement.
  • Lead Engineer level experience: setting technical direction, running work end to end, owning outcomes rather than tickets.
  • Practical daily use of AI-powered assistants (Claude Code, GitHub Copilot, Cursor) to improve productivity, quality or decision-making.
  • Fluent English, written and spoken.
    *Required: the right to work from within the European Union.

Nice to have:

  • AI-assisted engineering and agentic tooling applied to data onboarding and pipeline development
  • Data mesh concepts: data products, data contracts, domain ownership, federated governance
  • Kubernetes awareness sufficient to understand how the platform runs
  • A data platform enablement or internal developer experience background
  • High-volume operational or transactional environments where volume and latency both matter
  • GenAI applied structurally within the SDLC — defined workflows, prompt patterns, tool integrations
  • Genuine interest in agent-based workflows and AI-augmented development

Why Join Our Client

  • 100% remote. Fully distributed across Europe.
  • Trust over micromanagement. Senior engineers are treated as senior engineers.
  • A small team with real scope. Six engineers on a platform that changes how an entire organisation handles data.
  • AI-native delivery. Not experimenting — agentic tooling and AI assistants are built into how the work is done.
  • Visible expertise. Their engineers speak at conferences, publish, and run internal academies. Technical reputation is built here, not hidden.
  • Knowledge sharing is a stated value, not a slide.
  • Flexible engagement: permanent employment or B2B contract.

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📩 Apply now and include the reference number in the subject line: 19530 Senior Data Engineer,  or reach out to us directly for a confidential chat at +359898434743 – Peter.

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 Bendis Bridge HR
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