Data Engineer – Fulfillment & Logistics Data

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

📋 Description

• Design and maintain scalable data solutions and ETL/ELT pipelines for fulfillment and logistics operations.

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

• Create data models related to shipping, delivery, returns, refunds, and partner performance.

• Establish the data infrastructure for SLA monitoring, performance assessments, and dashboards.

• Supply fulfillment and tracking data to various product divisions and digital services, including Customer Service.

• Integrate event-driven data sources, such as Kafka.

• Guarantee data quality, governance, and privacy while consistently enhancing monitoring and quality assurance processes.

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

• Manage data products from the initial business requirements through to production operations.

• Actively engage in the Data Engineering discipline and assist in creating shared standards and collaborative practices.

⛳️ Requirements

• Multiple years of experience in Data Engineering or a similar role.

• Proficient in SQL and Python, with hands-on experience in ETL/ELT and data modeling.

• Familiarity with integrating operational or transactional systems and APIs.

• Experience with a contemporary data stack, ideally incorporating Snowflake, dbt, and Prefect.

• Knowledge of Kafka or similar event and streaming technologies.

• Understanding of AWS; experience with Infrastructure as Code using Pulumi or Terraform is a plus.

• Strong grasp of data quality and Data Governance principles.

• Proven experience working with cross-functional product or engineering teams.

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

• Proficient in German (at least B2 level) and fluent in English.

• Experience with order, fulfillment, logistics, or shipping data is a plus.

• Familiarity with OMS, carrier, or tracking systems and their interfaces is advantageous.

• Experience in SLA and performance monitoring or data-driven partner management is desirable.

• Knowledge of Data Mesh and domain-oriented data products is a bonus.

• Familiarity with BI tools such as Looker, Metabase, or Power BI is beneficial.

• Background in an e-commerce, marketplace, or platform environment is a plus.

🏝️ Benefits

• Flexible working hours.

• Options for remote work.

• Opportunities for professional development.

• Employee discounts.

• A modern data stack featuring Snowflake, dbt, Prefect, Kafka, AWS, and Pulumi.

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

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

• A shared Data Engineering practice that promotes knowledge exchange and established standards.