Senior Data Engineer (w/m/d) – Platform & Analytics

You will become part of a small, highly specialized data team (4 Engineers + Head of Data) that operates and further develops the central cloud data platform of the RSG Group – the data basis behind brands such as McFIT, JOHN REED and Gold's Gym.

Our team currently consists of colleagues with clear areas of expertise in governance & architecture, data science, AI/NLP, and MarTech. You will complement this setup as a technical all-rounder with in-depth engineering knowledge – someone who understands the platform end-to-end, bridges gaps between specialist areas, and raises the overall technical level.

This role includes the following areas of responsibility:

• Further develop the ELT platform: You will help shape our ELT pipeline from the largely automated source connection (Fivetran) through the transformation (Coalesce) to the data model in the Snowflake DWH – including performance, scalability and cost management.
• Data modeling with substance: You actively work on our modeling (Data Vault 2.0, Star/Snowflake Schema) and ensure that it remains maintainable and suitable for the entire enterprise – in close collaboration with our Architecture Lead.
• Predictive Use-Cases with Impact: Together with your DS/AI colleagues, you will develop and produce ML models along the Member Lifecycle (Churn, Retention, Propensity, Forecasting) – with a focus tailored to your profile.
• Data quality & governance in practice: You consistently implement established standards in the pipelines (Data Cataloging, Column-Level Lineage, GDPR compliance) and further develop them with the team.
• Single Source of Truth: You translate technical KPI definitions from controlling and specialist departments into sustainable, group-wide usable data models.
• DataOps: CI/CD, Testing, Monitoring, Alerting – you bring engineering best practices into everyday life.
• Stakeholder & Translation: You work directly with specialist departments, controlling and service providers, transforming technical requirements into viable technical solutions.
• Tech scouting: You evaluate new tools and patterns and, as an equal voice in the team, drive forward the technical target architecture – within the framework of the department's data strategy.

• 6+ years of professional experience in data engineering, including several years with real responsibility in a modern cloud data architecture.
• Completed studies (computer science, business informatics, statistics or similar) or comparable practical experience.
• Tech-Stack – Must-have:
  • SQL & Python – Development and operation of productive data pipelines
  • Snowflake (or comparable cloud DWH) – architecture, performance optimization and cost management
  • ELT stack – Fivetran, Coalesce, dbt or similar technologies
  • Data modeling – Data Vault 2.0, Star/Snowflake schema or similar methods
• Predictive Modelling: Experience in building and producing ML models (classification, forecasting) including feature engineering – you don't have to be a Research DS, but you should be comfortable with the entire model lifecycle.
• Governance & DataOps: Solid understanding of GDPR, lineage, cataloging, CI/CD, testing and Git in a data context.
• MarTech (basic understanding): Basic knowledge of Customer Data Platforms and Data Activation Stacks (e.g. Segment, Braze, Talon.One) as well as RESTful APIs and Webhooks.
• Structured way of working: Self-reliant, agile (2-week sprints), pragmatic.
• Communication: You can speak to the specialist department and controlling on an equal footing and explain technical topics in a way that is appropriate for the target audience.
• Language skills: You communicate confidently in German (at least B2 level) and can easily understand, create and discuss technical topics and documentation in English.