Data Engineer – Fulfillment & Logistics Data

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

📋 Description

• Design and manage scalable data products along with ETL and ELT pipelines for logistics and fulfillment processes.

• Consolidate data from order management systems, marketplaces, shipping providers, and tracking platforms.

• Create data models associated with shipping, delivery, returns, refunds, and partner performance.

• Lay down the data infrastructure for SLA monitoring, performance assessments, and dashboard creation.

• Deliver fulfillment and tracking information to other product divisions and digital services, such as Customer Service.

• Integrate event-driven data sources, including Kafka.

• Ensure high standards of data quality, governance, and privacy.

• Enhance monitoring processes and quality assurance checks.

• Collaborate closely with Product Management, Engineering, and Operations teams.

• Take ownership of data products from initial business requirements through to operational production.

• Actively engage in the Data Engineering practice, contributing to the development of shared standards and methodologies.

⛳️ Requirements

• Several years of experience in Data Engineering or a similar position.

• Proficient in SQL and Python.

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

• Familiarity with integrating operational or transactional systems and APIs.

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

• Knowledge of Kafka or similar event and streaming technologies.

• Understanding of AWS.

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

• Strong grasp of data quality principles and Data Governance.

• Experience working collaboratively with cross-functional product or development teams.

• Independent, organized, and solution-focused work approach.

• Proficiency in German at least at B2 level and fluent in English.

• Nice to have: Background in order, fulfillment, logistics, or shipping data.

• Nice to have: Familiarity with OMS, carrier, or tracking systems and their integrations.

• Nice to have: Experience with SLA and performance monitoring or data-driven partner management.

• Nice to have: Understanding 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.

• Opportunity for mobile work.

• Professional development opportunities.

• Employee discounts.

• Additional benefits.

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

• Direct influence on fulfillment efficiency, delivery quality, and partner performance.

• Close cooperation with Product, Engineering, and Operations teams.

• A collaborative Data Engineering practice that promotes knowledge sharing and established standards.