Your mission

Everything Rocket does — AI extraction, pricing intelligence, customer dashboards, business reporting — runs on data that you make trustworthy. You will build and operate the pipelines that pull sales data out of heterogeneous hotel systems (PMS, CRM, email) and land it, cleaned and modeled, in our Databricks lakehouse.

The core of the job: Hotel data is famously messy: every property configures its PMS differently, legacy systems export inconsistent formats, and the same booking looks different in three systems. Making that reliable at scale is the job.

• Ingestion pipelines. Build and maintain pipelines from customer systems (SIHOT, Opera, Guestline, Salesforce, email) into our bronze layer — batch and streaming, APIs and file-based, resilient to the quirks of each source.
• Data modeling. Develop the silver/gold layers of our Medallion architecture: clean, well-documented models of requests, offers, bookings, and revenue that serve analytics, dashboards, and ML features alike.
• Data quality and observability. Implement validation, monitoring, and alerting so broken source data is caught before it reaches a customer dashboard or a pricing model.
• Analytics enablement. Support customer-facing performance reports and internal KPI dashboards — working with Product and customer teams to turn data into insight hotels act on.

What success looks like:

• 3 months: You own several production pipelines end-to-end and have measurably improved their reliability.
• 12 months: Onboarding a new hotel group’s data is a repeatable process, not a project — and data quality issues are caught by your systems, not by customers.

Your profile

• 2–4 years as a data engineer or in a strongly data-focused engineering role
• Strong SQL and Python
• Hands-on Databricks and Spark experience — this is a hard requirement, our entire platform runs on it
• Hands-on experience building production pipelines (batch and/or streaming)
• Pragmatic approach to messy real-world data
• Strong English (B2–C1), German (min. B2)
  

Nice to have, not required:

• Medallion / lakehouse architecture experience
• API-based ingestion from enterprise systems (CRM, ERP, PMS)
• dbt, Delta Live Tables, or similar transformation tooling
• BI/dashboard experience (Chart.js, Power BI, or similar)

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.