Senior Data Platform Engineer in Berlin

A fast-growing European software group serving tens of thousands of trades and construction businesses across Germany, Austria and Switzerland is building a next-generation, cloud native, AI native data platform underneath its existing products: one governed model that data from every product lands into and conforms to, serving both reporting and AI.

This is one of the data team's first hires, built doers first with no leadership layer yet, so you'll help decide the architecture directly alongside the CTO.

You'll own the path from a production source database to the raw landing zone: change data capture, transport, and landing.

What you build for the first source becomes the pattern every source after it reuses, so getting it right once matters more than getting it done fast.

• What you'll be doing
• Architect and build change data capture against real production databases, choosing between log-based capture, a transactional outbox, change tables or a polled change flag depending on what each source will actually give you.
• Extract from systems that were never designed to be extracted from, working from observed behaviour when the documentation runs out.
• Design landing and transport that keeps full fidelity and reconciles cleanly back against its source.
• Build for replay and for being wrong: pipelines that rerun without drama, not pipelines that only work once.
• Own what you build through backfills, schema changes and the 3am failure, not just the design phase.
• Set the pattern the next source, and the engineer who builds it, will follow.
• Use agentic coding tools on real, complex work: decompose it, iterate, and review what comes out to the same standard as any other code.

What we're looking for

• 6+ years building and running production data pipelines across multiple systems, with real scars from backfills and failures, not just design work.
• Hands-on change data capture experience, and the ability to explain the trade-offs you weighed and why.
• Strong SQL and strong data modelling: you reason about grain, keys, late-arriving data and idempotency without being prompted.
• Comfortable on a cloud platform without needing to own it: containerised workloads, infrastructure as code, your own delivery pipeline.
• A genuine bar on data protection and tenant separation, designed in rather than bolted on afterwards.
• Hands-on, established use of agentic coding tools on complex work.
• A track record of making the people around you better, we'll ask for specifics.
• Nice to have
• Streaming or event infrastructure, particularly durable, replayable message transport.
• Experience extracting from source systems you don't control.
• Data governance, lineage or catalog tooling applied to pipelines that were already live.
• Experience in trades, construction or a comparable vertical.
• German fluency.
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