Data Engineer (f/m/div.)

Your contribution to something big:
As a Data Engineer, you will build scalable data solutions that digitalize procurement processes and enable AI-driven initiatives. Working in an international team, you will turn business needs into reliable, high-quality data products.
Build and operate scalable data solutions: Develop, maintain and continuously improve automated ETL pipelines, data products and data models that support digital procurement and AI use cases.
Turn business needs into data solutions: Translate customer and stakeholder requirements into robust data transformations and models that enable reporting, analytics and informed decision-making.
Ensure data quality and reliability: Establish and continuously improve data integrity, security and quality by working closely with data producers and consumers.
Enable data-driven decisions: Support ad-hoc analyses and develop solutions that can be documented, scaled and reused across the organization.
Drive reliable data operations: Apply DevOps principles to ensure the stability, monitoring and continuous improvement of automated data pipelines, including data testing, CI/CD and KPI tracking.
Collaborate internationally: Work closely with project management, customers, IT teams and other stakeholders, balancing business needs with technical and organizational frameworks.
Bring a service-oriented mindset: Act as a trusted partner for data consumers and stakeholders, focusing on practical solutions and measurable business value.
Explore the future of AI: Stay informed about the latest developments in Generative AI, including agentic AI, and identify opportunities to apply these technologies to real-world business challenges.
What distinguishes you:
Education: Master's degree in Computer Science or a related field, or equivalent professional experience.
Experience
5+ years of professional experience in data engineering, data modeling, ETL processes and data warehouses/lakehouses.
Experience designing and operating automated data pipelines and scalable data solutions.
Practical experience working with data and analytics platforms such as Databricks, Power BI or Tableau.
Know-how:
Strong proficiency in SQL; experience with Python is an advantage.
Solid understanding of data modeling, ETL/ELT processes, data warehouses and lakehouses.
Proven knowledge of DevOps principles, including data testing, CI/CD, monitoring, KPI definition and tracking.
Understanding of agile software development practices.
Knowledge of current developments in Generative AI and agentic AI, with an interest in applying them to real-world business challenges.
Ability to design technical concepts and communicate them clearly to both technical and non-technical audiences.
Working Style and Methods:
Analytical, structured and solution-oriented.
Strong stakeholder and project management skills.
Collaborative and service-oriented mindset.
Personality:
Curious, adaptable and eager to turn new technologies into practical solutions.
Languages: Excellent English communication skills.

Employment type
Full-time

Work arrangement
Hybrid