Aufgaben
* Design, build, and optimize batch data pipelines for internal tool use cases
* Develop efficient Spark SQL transformations for large-scale datasets
* Use Python for data processing, orchestration, and automation
* Create and maintain data models (facts, dimensions, aggregates) with clear grain and metric definitions
* Ensure data quality and correctness, including handling late data, duplicates, and adjustments
* Implement validation, data quality checks, and reconciliation logic
* Work with business stakeholders to gather requirements, define metrics, and translate needs into pipelines
* Collaborate with infrastructure teams on standards, performance tuning, and best practices
Profil
* Bachelor oder Master degree in a technical field or an equivalent qualification
* Experience in data engineering or a related field
* Strong proficiency in Spark SQL for large-scale data transformations
* Solid Python skills for data processing and pipeline development
* Strong understanding of data modeling (fact tables, dimensions, grain, SCDs)
* Hands-on experience building and maintaining batch pipelines in production
* High attention to detail with a strong focus on data quality and metric integrity
* Ability to communicate clearly with non-technical stakeholders and translate business needs into data solutions
Benefits
* Remuneration in the most attractive collective agreement in the industry
* Annual leave entitlement of 30 days
* Generous working time account with the possibility to pay overtime
* Subsidization of direct insurance (as company pension scheme)