Data Engineer – Product, Pricing & Inventory Data

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

📋 Description

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

• Integrate data from Product Information Management (PIM) systems, marketplaces, external content sources, and various operational systems into the data platform.

• Structure and model data pertaining to products, attributes, assortments, prices, and inventory.

• Ensure transparency regarding data quality, completeness, timeliness, and accessibility.

• Create effective quality checks and monitoring solutions.

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

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

• Uphold data governance, traceability, and uniform data standards.

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

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

• Actively engage in the Data Engineering practice and contribute to the establishment of shared standards and methodologies.

⛳️ Requirements

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

• Strong proficiency in SQL and Python.

• Familiarity with ETL/ELT processes and data modeling.

• Experience with contemporary data stacks, ideally including Snowflake, dbt, and Prefect.

• Knowledge of Kafka or similar event-driven and streaming technologies.

• Understanding of AWS.

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

• In-depth understanding of data quality, governance, and the handling of large, varied datasets.

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

• An independent, organized, and solution-focused work approach.

• Proficient in German at least at a 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 with data quality monitoring, data observability, or data mesh.

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

• Nice to have: Familiarity with BI tools such as Looker, Metabase, or Power BI.

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

🏝️ Benefits

• Flexible working hours.

• Options for remote work.

• Opportunities for professional development.

• Employee discounts.

• Additional benefits.