Data & Analytics Engineer (m/f/d)

• Design, implement, and maintain backend services in Python that power our data access and distribution layer
• Build and operate automated build, test, and deployment pipelines following CI/CD and GitOps practices, running on AWS and Kubernetes
• Design and maintain data models and schemas (Avro, SQL) for our data pipelines and services, and publish them to downstream consumers via our Kafka-based distribution platform and schema registry
• Build access-layer data models in our analytics environment (e.g., Snowflake) so applications can work with the data directly, including via API
• Act as the coordination interface between the Data and Tech divisions, aligning priorities, schemas, and timelines across upstream and downstream teams

Your profile

• 3+ years of experience in analytics engineering, data engineering, or a related role.
• Strong SQL skills and solid experience in data modeling (e.g., dimensional modeling, star schemas).
• Hands-on experience with event streaming and message distribution, ideally Kafka, including schema management with the Kafka schema registry (Avro, Protobuf, or JSON Schema).
• Experience designing data contracts and schemas between upstream producers and downstream consumers.
• Experience with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and modern data stack tools (e.g., dbt, CI/CD).
• Openness to AI-assisted development workflows (e.g., Claude Code or similar).
• Comfort working at the boundary of streaming/operational data and analytical data models, and building access layers that serve applications via API.
• Strong attention to detail with a quality-focused and structured working style.
• Interest in data governance, standards, and scalable data architecture.
• Analytical mindset with strong problem-solving skills.
• Excellent communication skills in English (German is a plus), with both technical and business stakeholders, combined with a solid understanding of business requirements and contexts.