Data Engineer
Role details
Job location
Tech stack
Job description
As a Data Engineer, you will join a growing central data engineering team supporting the digital transformation of globally recognized brands such as Salomon, Arc'teryx, Peak Performance, Atomic, and Wilson. You will work in a federated, multi-brand environment, building scalable and reliable data products on the Databricks platform while collaborating closely with experienced engineers and business stakeholders across regions., * Building and maintaining scalable data pipelines and ingestion frameworks using Databricks, Delta Live Tables, Auto Loader, and Apache Spark.
- Developing reliable and well-documented data products across the Medallion architecture (Bronze, Silver, Gold layers).
- Delivering data assets consumable through Unity Catalog, Databricks SQL, and Power BI.
- Optimizing data pipelines for performance, scalability, reliability, and cost efficiency.
- Implementing data quality monitoring, governance standards, and pipeline observability.
- Collaborating with global brand and regional teams to translate business requirements into reusable data solutions.
- Applying engineering best practices, including Git-based workflows, CI/CD principles, code reviews, testing, and documentation.
- Contributing to the continuous evolution of the enterprise data platform and data engineering standards.
- Supporting incident resolution, troubleshooting, and ongoing platform improvements.
- You will report to the Director of Data Engineering., * Phone screening: A conversation with Amer Sports' HR manager to discuss the role, our organization, and your expectations.
- Interviews: Usually 2-4 rounds, including interviews with the hiring manager and prospective team.
- Feedback and decision: We aim to provide feedback throughout the process.
Requirements
Do you have experience in Unity?, Do you have a Bachelor's degree?, * Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field (or equivalent practical experience).
- 2-4 years of experience in data engineering, including hands-on work with Databricks or Apache Spark in a professional environment.
- Experience building and maintaining pipelines across Medallion architecture layers (Bronze, Silver, Gold).
- Experience working with enterprise or cloud-based source systems; SAP/S4HANA experience is considered an advantage.
- Experience working in cloud environments, preferably Microsoft Azure., * Strong practical knowledge of Databricks, including Delta Live Tables, Auto Loader, Workflows, Unity Catalog, and Databricks SQL.
- Solid experience with Apache Spark (PySpark), Delta Lake, Python, and SQL.
- Familiarity with Azure services such as Azure Data Factory, Azure Blob Storage / ADLS, and Azure DevOps.
- Understanding of Git-based workflows, CI/CD practices, and software engineering standards.
- Experience with data quality monitoring and governance tooling.
- Basic understanding of interoperability patterns such as Delta Sharing, APIs, and cloud-based data integrations., * Strong analytical and problem-solving skills with attention to quality and detail.
- Structured and delivery-focused mindset with the ability to work independently and reliably.
- Clear communication and documentation skills.
- Collaborative approach and willingness to work across international teams and functions.
- Curiosity and eagerness to continuously learn and develop technical expertise.
- Pragmatic and solution-oriented approach to challenges.
- Motivation to contribute to impactful data solutions supporting healthier, more active lives., * Professional proficiency in English is required.
- Preferred certifications (not mandatory):
- Databricks Certified Data Engineer Associate
- Microsoft Azure Data Engineer Associate (DP-203)
- Azure Fundamentals
What we consider a plus
- Experience with SAP ERP or SAP S/4HANA integrations.
- Familiarity with Power BI Direct Lake or analytical consumption models.
- Exposure to Snowflake, SAP Datasphere, Delta Sharing, or other modern data-sharing technologies.
- Basic knowledge of German is beneficial, but not required.