Data Engineer (m|f|d)

As the asset manager of Munich Re and ERGO, MEAG makes a significant contribution to the success of Munich Re Group. Our staff bring together peerless know-how in all the relevant asset classes and are the driving force behind our success as one of the world's top asset managers.   We are seeking a skilled and motivated Data Engineer to join our Data Enablement Team within the (Gen)AI Transformation Management department. The Data Enablement Team manages data architecture, pipelines and governance (incl. compliance) to enable the creation of AI agents powering impactful AI use cases that will enhance our business every day. 

Your main responsibilities:

• Define the data structure and quality for processing of structured data
• Align requirements of data pipelines for structured data with Munich RE IT 
• Develop data cubes for insight generation
• Ensure compatibility between structured data and (Gen)AI model requirements
• Develop and maintain high-quality documentation of data sources, data flows, and data assets to facilitate knowledge sharing and collaboration across the organization
• Work closely with business stakeholders, data scientists, engineers, and other teams to understand data requirements, provide data support, and identify opportunities for data-driven innovation
• Stay up-to-date with emerging trends, technologies, and methodologies in data management, AI, and ML, and apply this knowledge to continuously improve data enabler services and capabilities

Your profile:

•  Master’s degree in computer science or a related field
• Several years of experience with working with traditional AI or GenAI solutions

• 3+ years of working experience in data engineering 
• Proficiency in data wrangling, data pipeline mgmt., and data quality frameworks/best practices
• Expertise in programming languages (e.g., Python, C++), query languages (e.g., SQL), and familiarity with big data tools (e.g., Apache Spark) and cloud platforms (e.g., Azure)
• Experience working with un-/structured data (ideally both) to ensure compatibility with model requirements, e.g.:
  • Structured data: Experience in creating data models, -cubes, and relationship mapping between datasets 
  • Unstructured data: Skills in transforming data into vector embeddings and feature tables, proficiency in using tools for data annotation and metadata tagging (e.g., Dataloop AI, AWS SageMaker) 
• Very good communication, collaboration, and stakeholder management skills
• Ability to work in a fast-paced environment, prioritize tasks, and meet deadlines
• Business proficiency in English (C1) and German (C1) are required.

Benefits:

• Flexibility: Mobile work (option to work from home a few days a week), 30 days of vacation
• Asset Accumulation & Retirement Planning: Company pension system & employee savings plan
• Development: Intensive professional & personal development (internal & external offerings), LinkedIn Learning access 
• Health: Comprehensive company doctor services, Urban Sports cooperation 
• Family: pme family service, childcare allowance, care assistance, cooperation with daycare centers, flexible working hours
• Other: Daily free lunch in our cafeteria, Free hot drinks & water, "Deutschland Ticket Job" subsidy, Events, Underground parking garage with e-charging infrastructure & much more!

 

*Please note that this list is based on current collective agreements. These may change. The list is for information purposes only. We do not accept any liability for individual points. 

  MEAG stands not only for a partnership-based relationship with customers, but also for fair treatment of applicants and employees. Regardless of gender. So if we use the masculine form of personal designations, this is purely for the sake of readability. Applicants with disabilities will be given preferential consideration if they are otherwise essentially equally qualified.