Data Engineer

In this Data Engineer role, you’ll build scalable, secure data pipelines and analytics capabilities within Zurich’s Technology Delivery Center. You will work on cloud-based ETL, real-time data processing, and ML/AI-driven products, aligning architecture with business needs. The position offers collaboration across teams, exposure to modern MLops practices, and opportunities to influence data-driven decisions at a global insurer. This is a hands-on role at the intersection of data, cloud, and AI, with a strong impact on operational efficiency and innovation.

• flexible working model
• ability to work abroad up to 25 days yearly
• home office setup allowance
• training programs including English, German and Spanish
• health insurance
• life and accident insurance

• Architect and develop end-to-end scalable and secure data processes
• ETL data processing in AWS or cloud environments with Spark or Databricks (batch or real-time)
• MLEOPS and CI/CD: implement pipelines using Azure DevOps, Jenkins, etc.
• Develop microservices deployed in cloud environments
• Deploy with Docker, Kubernetes or similar technologies
• Define industrialisation and operational strategies for MLOps models
• Align business needs with technical requirements and architecture
• AI: develop products based on LLMs and fine-tuning techniques

• Python: 5 years of experience
• Cloud Engineering: 4 years (AWS, GCP, Azure)
• CI/CD & DevOps: 3 years building multi-cloud pipelines and automated deployments
• Microservices: 2 years designing and deploying distributed services
• Agentic AI / LLMs: 2 years integrating OpenAI, Anthropic, AI agents and MCP servers
• Backend Engineering: 2 years building APIs and end-to-end backend solutions

• collaborative mindset
• strong communication
• problem-solving orientation
• Advanced Python
• AWS
• Docker