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Our BI Engineering team builds the data foundations that power all business units across momox, from customer identity and marketplace integration to warehouse logistics and operational optimization. As a Senior Data Engineer, you will play a key role in creating scalable, reliable, and event-driven pipelines that integrate data from multiple applications and systems into our central data warehouse.

• Customer Identity & Data Integration: Build and maintain unified customer identity models across momox businesses (Books & Media, Fashion, etc.), ensuring consistent use of data for analytics and reporting
• Data Pipelines & Event Processing: Design, build, and optimize batch and streaming pipelines, leveraging Pub/Sub and BigQuery for real-time data flows
• Operational & Logistics Data: Develop metrics and pipelines that support warehouse efficiency
• ETL/ELT Development: Create and optimize robust data transformations, ensuring scalability, automation and reliability
• Performance & Observability: Monitor pipeline SLAs, improve performance through multiprocessing/event-driven workloads and implement automated data quality checks
• Collaboration & Ownership: Translate business requirements into technical solutions, collaborate with analysts and product teams and mentor junior engineers
• Best Practices & Strategy: Define data engineering standards, promote automation and efficiency and contribute to long-term architectural decisions

Our Tech Stack

• Data & Processing: GCP, BigQuery, Pub/Sub, Airflow, dbt
• Infrastructure: Kubernetes, Cloud Run
• Programming: Python (ETL/ELT, APIs, event processing, automation)
• Security & Cost Optimization: IAM, encryption, slot reservation, Policy Tags
• Versioning & CI/CD: GitLab CI, Terraform

• At least 5 years of proven experience as a Data Engineer or in a similar role (e.g., Data Warehouse Engineer, BI Engineer with strong data focus)
• Proven experience building scalable data pipelines (batch and streaming) in production environments
• Hands-on expertise with BigQuery (optimization, cost-efficient design, partitioning, clustering) and broader GCP ecosystem experience
• Platform and app deployments on Kubernetes (Airflow, Helm Chart, ArgoCD, Terraform)
• Strong skills in Pub/Sub and event-driven architectures (Eventarc, Cloud Run)
• Proficiency in Python for ETL/ELT development, APIs and automation
• Strong Airflow experience for workflow orchestration and dbt proficiency with dimensional modeling expertise
• Experience with data quality frameworks, automated testing and performance monitoring with observability practices
• Background in e-commerce, retail or multi-product environments with complex data integration needs
• Strong communication skills, collaborative mindset, and experience mentoring junior engineers and working with analytics teams

Lerne uns kennen!