Data Engineer (all genders)

Deine AufgabenEverything 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.

Dein Profil2–4 years as a data engineer or in a strongly data-focused engineering roleStrong SQL and PythonHands-on Databricks and Spark experience — this is a hard requirement, our entire platform runs on itHands-on experience building production pipelines (batch and/or streaming)Pragmatic approach to messy real-world dataStrong English (B2–C1), German (min.