Senior Data Engineer (all genders)

Your mission

Where the Data Engineer builds pipelines, you own the platform. Rocket’s data layer has to scale from a handful of European hotel groups to enterprise chains across two continents — multi-tenant, reliable, cost-efficient, and fast enough to serve both real-time product features and ML workloads.

You will set the architecture, the standards, and the roadmap for our Databricks lakehouse, and raise the bar for everyone working on data at MICE DESK.

• Data platform architecture. Own the design of our lakehouse (Medallion architecture on Databricks): tenancy model, storage layout, orchestration, streaming vs. batch strategy, cost management, and the evolution path as customer volume grows 10x.
• Scalable multi-tenant ingestion. Design the ingestion framework that makes onboarding a new hotel group a configuration task, not an engineering project — across wildly heterogeneous PMS/CRM sources and both EU and US data residency requirements.
• ML and product data serving. Build the interfaces between the data platform and its consumers: feature pipelines for our ML models, low-latency serving for in-product analytics, and the contracts that keep both stable.
• Standards and mentorship. Define engineering standards for the data team — testing, CI/CD for pipelines, documentation, data contracts — and mentor data engineers toward them.

What success looks like:

• 3 months: You’ve audited the current platform, set the target architecture, and shipped the first structural improvement.
• 12 months: The platform onboards new enterprise customers in days, serves ML and product reliably, and the data team operates at a visibly higher standard.

Your profile

• 
  
  • 5+ years in data engineering, including architecture ownership of a production data platform
  • Deep, hands-on Databricks and Spark expertise
  • Proven design of multi-tenant or large-scale data systems
  • Strong software engineering practice: testing, CI/CD, infrastructure-as-code for data
  • Experience mentoring engineers or leading data workstreams
  • Strong English (B2–C1), German (B2)

• Nice to have, not required:

  • Lakehouse/Medallion architecture at scale
  • Streaming architectures (Kafka, Delta Live Tables, structured streaming)
  • ML platform / feature store experience
  • EU data residency / GDPR-aware architecture experience
  • B2B SaaS background

Why us?

We are the technology company rethinking group and event sales in hospitality. What runs today through inboxes, spreadsheets and phone calls, our platform Rocket turns into one continuous, AI-supported process — from the first enquiry to the signed contract. European hotel groups already run their group sales on it.
What that means for you: you work with AI, not despite it. People who join us give feedback that shapes product decisions — and sooner or later come to understand why one prompt works better than another.
And because we are growing fast, a lot here is still taking shape. Sometimes the honest answer is “we’re still building that.” That is exactly where the opportunity lies: you will find open space rather than finished structures, and what you build here will carry your signature.

What we offer

• Work with real AI technology at international level — not as a pilot project, but as our business model.
• Genuine room to shape things. Your ideas do not land in a suggestion box; they land in the next iteration.
• A short path to the management team. Decisions take days, not committee rounds.
• Growth you are part of. We are building the company’s next chapter — with roles, responsibility and prospects that did not exist a year ago.
• Leipzig as your primary base, with regular time in the office and flexible remote work. Hybrid models are everyday practice here, not the exception.
• Permanent contract, full-time.
• Performance bonuses for demonstrable results.
• Multi-day team events in places that are actually fun.

Our hiring process

Intro interview — we get to know each other, and you learn where we stand and where we are heading.

Case study or technical study, depending on the role — a real problem from our day-to-day that we work through together.

Interview with your future manager and, depending on the position, with our founders.

From the first conversation to a decision takes at most two weeks. And you will hear from us either way — including when it is not a fit this time.