Senior Data Engineer

Quick Facts

• Focus: AI-enabled data engineering and GenAI/MLOps for insurance use cases

Description

You will develop and implement strategic digitalization projects that use AI across the insurance value chain. The role involves preparing and integrating large volumes of structured, semi-structured, and unstructured data for GenAI solutions, and contributing to productive deployment and operations of ML/GenAI solutions through MLOps. You will also design, implement, and operate scalable data-management and GenAI solutions in cloud environments, and support operational teams in enhancing ML/GenAI applications.

Responsibilities

• Develop and implement AI-driven digitalization initiatives across the insurance value chain

• Integrate and prepare structured, semi-structured, and unstructured data from diverse sources

• Deploy, operate, and improve ML and GenAI solutions using MLOps

• Design and run scalable data-management and GenAI solutions in cloud environments

• Advise operational units to enable and further enhance ML/GenAI applications

Requirements

• Fluency in English

• Degree in natural sciences, (applied) mathematics, computer science, business informatics, or related field

• Strong knowledge and experience in data modeling and data visualization with scalable data management concepts

• Experience with standardized ETL processes and data pipelines

• Practical experience putting data solutions and MLOps into production

• Strong knowledge of one or more of: Python, Spark, SQL; plus version control (e.g., GitHub) and cloud technologies (e.g., Azure/AWS)

• Experience designing and implementing solutions using classical ML, LLMs, RAG architectures, and agent-based systems

• Proactive, innovative mindset with ability to think and act in a networked way

• Willingness to travel

• Preferably: insurance industry experience

Benefits

• Medical package, sports card, and sports sections

• Flexible working hours, confidential employee assistant program, and possibility of remote working

• Training, workshops, hackathons, meetups, digital learning platforms, and language courses

• CSR activities

• Team activities (e.g., bike races, soccer matches, film marathons)

• Diversity and equal opportunity regardless of gender, nationality, beliefs, disability, age, or sexual orientation/identity