Data Engineer – Commerce and Customer Data

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

📋 Description

• Design and manage scalable data products as well as ETL and ELT pipelines tailored for commerce and customer domains.

• Structure data from checkout, orders, payments, customer interactions, loyalty programs, and customer service systems.

• Provide data accessibility to product teams and analytics departments.

• Merge data from various systems and event-driven sources, including integration via Kafka.

• Create high-performance, transparent, and reusable data models utilizing the modern data stack.

• Uphold data quality, governance, and privacy standards, especially concerning personal customer and payment information.

• Collaborate closely with Product Management, Software Engineering, Data, and Business teams.

• Take ownership of data products from requirement gathering to production operations.

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

⛳️ Requirements

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

• Extensive expertise in SQL and Python.

• Proficiency 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 the management of personal data.

• Proven track record of working with cross-functional product or development teams.

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

• Proficiency in German at a minimum of B2 level and strong English communication skills.

• Nice to have: Experience in e-commerce, checkout, order, or payment data.

• Nice to have: Knowledge of customer data, CRM, loyalty, or customer service domains.

• Nice to have: Familiarity with Data Mesh and domain-oriented data products.

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

• Nice to have: Experience in building data pipelines for AI or machine learning applications.

🏝️ Benefits

• Flexible working hours.

• Options for remote and mobile work.

• Opportunities for professional development.

• Employee discounts.

• Additional benefits.