Data Engineer

OverviewIn 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.Compensaciones / Beneficiosflexible working modelability to work abroad up to 25 days yearlyhome office setup allowancetraining programs including English, German and Spanishhealth insurancelife and accident insuranceResponsabilidadesArchitect and develop end-to-end scalable and secure data processesETL 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 environmentsDeploy with Docker, Kubernetes or similar technologiesDefine industrialisation and operational strategies for MLOps modelsAlign business needs with technical requirements and architectureAI: develop products based on LLMs and fine-tuning techniquesRequisitos principalesPython: 5 years of experienceCloud Engineering: 4 years (AWS, GCP, Azure)CI/CD & DevOps: 3 years building multi-cloud pipelines and automated deploymentsMicroservices: 2 years designing and deploying distributed servicesAgentic AI / LLMs: 2 years integrating OpenAI, Anthropic, AI agents and MCP serversBackend Engineering: 2 years building APIs and end-to-end backend solutionscollaborative mindsetstrong communicationproblem-solving orientationAdvanced PythonAWSDocker

Requisitos principalesPython: 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