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.

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

• Organize and model data related to products, attributes, assortments, prices, and inventory.

• Enhance transparency regarding data quality, completeness, timeliness, and availability.

• Create quality assurance checks and monitoring solutions.

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

• Integrate event-driven data sources, including Kafka.

• Ensure adherence to data governance, traceability, and uniform data standards.

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

• Assume responsibility for data products from business requirements to production operations.

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

⛳️ Requirements

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

• Extensive knowledge of SQL and Python.

• Proficient 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.

• Knowledge of AWS.

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

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

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

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

• Proficiency in German at a minimum of B2 level.

• Strong command of English.

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

• Nice to have: Familiarity with pricing, inventory, or availability data.

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

• Nice to have: Background in market, competitor, or pricing data analysis.

• 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 remote work.

• Opportunities for professional development.

• Employee discounts.

• Additional benefits.

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

• A direct impact on the quality, timeliness, and availability of essential product, pricing, and inventory data.

• Close collaboration with Product, Engineering, and business teams across assortment, content, and pricing.

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