As a Data Engineer at the Miele X Data & Analytics group, your goal is to implement innovative solutions for our data engineering projects to enable rapid experimentation, increase the accuracy of our models, algorithms and systems and ensure high data quality to transform Miele X’s products and customer experience. There are numerous exciting challenges and opportunities in various themes. You will work with the team to build a modern, automated and data engineering-centric function for your colleagues in marketing, product, e-commerce, and operations to get X done.

Putting the customer at the forefront of our thinking and building world-class data and digital products that combine state-of-the-art data, processes, models, algorithms, and systems that are ‘forever better’ is paramount for the team. Delivering the best data and analytics experience possible. To as many people as possible. In as many moments as possible is what we do every day at MXA D&A group.

• Following the policy and standards for the Data Platform set by the Head of Data Integration and the Data Architect. Making sure data is provided properly, to the right people, is of the highest possible quality and that all PII data is treated according to GDPR and local legislation where applicable.
• Building, improving and maintaining the data pipelines and Data Platform.
• Inspiring and supporting the Data Integration Team to realize an optimal contribution to the end result of the organization.
• Ensuring a high standard of quality (E.g. employee satisfaction, overall data integration / availability performance, customer satisfaction, efficient and effective processes).
• Creating synergy within the entire organization by striving for optimal performance, connections and mutual commitment between individual business units.

• At least 5 years experience as a data engineer.
• Fluent in English.
• Expert SQL knowledge.
• Good knowledge of data engineering standards.
• Good knowledge of the Azure data platform, such as Azure Data Factory, Azure SQL, Azure Synapse Analytics, Azure Data Lake Storage, and other modern cloud data platforms.
• Good knowledge of data warehousing.
• Good knowledge of GIT for version control.
• Experience with CI/CD concepts such as deployment pipelines.
• It's beneficial to have experience with the following: Apache Spark, Python, Databricks, Airflow.