Senior Data Engineer

Senior Data Engineer (m/f/d)

Hybrid/ Garching near Munich

We’re looking for Senior Data Engineer for Amer Sports’ office in Garching near Munich.

Amer Sports is a global collective of iconic sports and outdoor brands, powered by a community of people who share a passion for authenticity, impact, and excellence. We bring together leading brands, talented teams, and a culture built on collaboration. If you’re looking for an environment where you can make an impact and grow your career, we invite you to explore the opportunity below.

In this role, you will build the data foundations that power critical business decisions across Procurement, Supply Chain and Operations. Working with technologies such as Databricks, SAP Datasphere and Azure, you will design scalable data products that transform complex SAP and non-SAP data into trusted insights, advanced analytics and AI-ready datasets.

This is an opportunity to work on large-scale global data challenges, collaborate with international stakeholders, and have a direct impact on how data is used across some of the world's most recognized sports and outdoor brands.

What you will be doing

• Build scalable data pipelines
• Design and develop robust data pipelines integrating SAP and non-SAP systems.
• Build and maintain modern data processing solutions using Databricks and cloud technologies.
• Enable seamless access to trusted business data across procurement, operations and analytics functions.

Create reusable data products

• Design reusable data models covering procurement, vendor, contract, logistics and operational datasets.
• Implement Medallion Architecture (Bronze, Silver, Gold) to support scalable analytics and reporting.
• Deliver consumption-ready datasets for self-service analytics and decision-making.

Ensure governance, quality and trust

• Implement automated data quality checks and monitoring processes.
• Maintain data lineage, metadata standards and governance frameworks.
• Support secure access controls and data protection standards across analytical environments.

Enable advanced analytics and AI

• Develop feature-ready data products that support spend analytics, supplier performance, risk management and AI-driven use cases.
• Collaborate with data analysts, business stakeholders and data scientists to create scalable analytical solutions.
• Continuously improve data accessibility and usability across the organization.

Partner with business stakeholders

• Work closely with Procurement, Supply Chain, Operations and Analytics teams to understand business needs.
• Translate complex requirements into scalable technical solutions.
• Act as a trusted partner and technical advisor in driving data-driven decision making.

Contribute to engineering excellence

• Apply modern software engineering practices including Git-based development, CI/CD and automated testing.
• Support the evolution of enterprise data platform standards and best practices.
• Share knowledge an