Data Engineer – Commerce & Customer Data

This is a fully remote position, open to applicants in Germany.

📋 Description

• Create and manage scalable data products alongside ETL and ELT pipelines targeted at commerce and customer sectors.

• Structure data from various domains such as checkout, orders, payments, customer information, loyalty programs, and customer support.

• Deliver data to product teams and analytics departments.

• Integrate data from multiple systems and event-driven sources, including those using Kafka.

• Design high-performance, traceable, and reusable data models utilizing the modern data stack.

• Maintain data quality, governance, and privacy, especially regarding personal customer and payment information.

• Collaborate closely with Product Management, Software Engineering, Data, and Business teams.

• Take ownership of data products from the initial requirements gathering phase through to production operations.

• Actively participate in the Data Engineering Practice and assist in the development of shared standards and methodologies.

⛳️ Requirements

• Multiple years of experience in data engineering or a similar position.

• Strong proficiency in SQL and Python.

• Familiarity with ETL/ELT processes and data modeling techniques.

• Experience working with a modern data stack, preferably including Snowflake, dbt, and Prefect.

• Knowledge of Kafka or similar event-driven and streaming technologies.

• Understanding of AWS.

• Preferably, experience with Infrastructure as Code tools like Pulumi or Terraform.

• Solid grasp of data quality, governance, and the management of personal data.

• Experience in collaborating with cross-functional product or engineering teams.

• An independent, organized, and solution-focused approach to work.

• Proficiency in German at a minimum B2 level.

• Strong command of English.

• Nice to have: Experience related to e-commerce, checkout, order, or payment data.

• Nice to have: Familiarity with customer data, CRM, loyalty programs, or customer service.

• Nice to have: Experience with Data Mesh and domain-oriented data products.

• Nice to have: Knowledge of BI tools such as Looker, Metabase, or Power BI.

• Nice to have: Experience in building data pipelines for AI or machine learning projects.

🏝️ Benefits

• Flexible working hours.

• Options for remote work.

• Opportunities for professional development.

• Employee discounts.

• Additional benefits.

• Access to a modern data stack that includes Snowflake, dbt, Prefect, Kafka, AWS, and Pulumi.

• The chance to make a direct impact on key commerce and customer processes at INTERSPORT.

• Work within cross-functional product teams with strong collaboration across Data, Engineering, and Product.

• Engage in a shared Data Engineering Practice that promotes professional knowledge exchange and sets clear standards.