Data Engineer – Fulfillment & Logistics Data
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Job Description
Data Engineer building fulfillment and logistics data products for INTERSPORT’s e-commerce platform. Developing pipelines, data models, and tracking integrations for orders, deliveries, returns, and partner performance.
Responsibilities:
- Develop and operate scalable data products as well as ETL and ELT pipelines for fulfillment and logistics processes
- Integrate data from order management systems, marketplaces, shipping providers, and tracking systems
- Model data related to shipping, delivery, returns, refunds, and partner performance
- Establish the data foundation for SLA monitoring, performance analysis, and dashboards
- Provide fulfillment and tracking data to other product areas and digital services such as Customer Service
- Integrate event-based data sources, including Kafka
- Ensure data quality, governance, and privacy
- Further develop monitoring and quality checks
- Work closely with Product Management, Engineering, and Operations
- Own data products from business requirements through production operation
- Actively contribute to the Data Engineering practice and help develop shared standards and ways of working
Requirements:
- Several years of experience in Data Engineering or a comparable role
- Advanced knowledge of SQL and Python
- Experience with ETL/ELT and data modeling
- Experience integrating operational or transactional systems and APIs
- Experience with a modern data stack, ideally Snowflake, dbt, and Prefect
- Experience with Kafka or comparable event and streaming technologies
- Knowledge of AWS
- Ideally, experience with Infrastructure as Code using Pulumi or Terraform
- Good understanding of data quality and Data Governance
- Experience collaborating with cross-functional product or development teams
- Independent, structured, and solution-oriented approach to work
- German at least at B2 level and fluent English
- Nice to have: Experience with order, fulfillment, logistics, or shipping data
- Nice to have: Knowledge of OMS, carrier, or tracking systems and their interfaces
- Nice to have: Experience with SLA and performance monitoring or data-driven partner management
- Nice to have: Knowledge of Data Mesh and domain-oriented data products
- Nice to have: Experience with BI tools such as Looker, Metabase, or Power BI
- Nice to have: Experience in e-commerce, marketplace, or platform environments
Benefits:
- Flexible working hours
- Mobile working
- Professional development opportunities
- Employee discounts
- Additional benefits
- Modern data stack featuring Snowflake, dbt, Prefect, Kafka, AWS, and Pulumi
- Direct impact on fulfillment efficiency, delivery quality, and partner performance
- Close collaboration with Product, Engineering, and Operations
- Collaborative Data Engineering practice with knowledge sharing and clear standards
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