Data Engineer – Product, Pricing & Inventory Data

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

📋 Description

• Design and manage scalable data products and ETL/ELT pipelines for product, pricing, and inventory information.

• Incorporate data from PIM systems, marketplaces, external content sources, and various operational systems into the Data Platform.

• Organize and model data pertaining to products, attributes, assortments, pricing, and inventory.

• Ensure transparency regarding data quality, completeness, freshness, and availability.

• Create suitable quality assurance checks and monitoring solutions.

• Consistently provide data products for discovery, checkout, and fulfillment processes.

• Integrate event-driven data sources, including Kafka.

• Maintain data governance, traceability, and adherence to consistent data standards.

• Collaborate closely with Product Management, Engineering, Category, Content, and Pricing teams.

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

• Proactively engage in the Data Engineering Practice and contribute to the ongoing enhancement of shared standards and working methods.

⛳️ Requirements

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

• Proficient knowledge of SQL and Python.

• Experience in ETL/ELT processes and data modeling.

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

• Experience with Kafka or similar event-driven and streaming technologies.

• Understanding of AWS.

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

• Strong grasp of data quality, data governance, and handling large, diverse datasets.

• Proven ability to collaborate with cross-functional product or engineering teams.

• An independent, structured, and solutions-oriented work approach.

• Proficient in German at a minimum B2 level and fluent in English.

• Nice to have: Experience with product data, PIM systems, or classification standards.

• Nice to have: Knowledge of pricing, inventory, or availability data.

• Nice to have: Experience in data quality monitoring, data observability, or data mesh.

• Nice to have: Familiarity with market, competitor, or pricing data.

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

• Nice to have: Experience in e-commerce, marketplace, or retail settings.

🏝️ Benefits

• Flexible working hours.

• Options for mobile working.

• Opportunities for professional development.

• Employee discounts.

• Additional benefits.

• Modern data stack that includes Snowflake, dbt, Prefect, Kafka, AWS, and Pulumi.

• Direct influence on the quality, freshness, and accessibility of essential product, pricing, and inventory data.

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

• A collaborative Data Engineering Practice that emphasizes knowledge sharing and clear standards.