Job Description

Location

Munich, Germany

Work mode

Hybrid

Job level

Professional

Job ID

6157-1952

Company

MEAG

Employment type

Not available

Area of expertise

Data, BI & Analytics

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 Product Owner 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, as well as the fulfillment of data analytics and reporting requirements.

Your main responsibilities:

Own the design and delivery of scalable data products that support AI, analytics, and reporting requirements Align data pipeline requirements with Munich Re IT Design and develope data structures (e.g., data cubes) that ensure high quality and scalability Ensure compatibility between structured data and GenAI model requirements Develop and implement a data architecture and governance model for MEAG Maintain high-quality documentation of data sources, flows, and assets to support transparency and collaboration Collaborate with business stakeholders, data scientists, engineers, and other teams to identify opportunities for data-driven innovation Stay current with emerging trends, technologies, and methodologies in data management, AI, and ML to continuously improve data enablement capabilities

Your profile:

Master’s degree in data science, computer science, statistics, or a related field 5+ years of professional experience in data engineering or data-centric product development, ideally in complex environments involving data warehouses or cloud platforms Strong expertise in data modeling, pipeline orchestration, and data quality frameworks Solid programming skills in Python and SQL, with experience in big data tools (e.g., Apache Spark, Hadoop) and cloud platforms (e.g., Azure, AWS, GCP) Experience working with both structured and unstructured data: + Structured data: Proficient in designing and optimizing data models, cubes, and relational mappings
+ Unstructured data: Skilled in transforming raw data into usable formats (e.g., embeddings, feature tables), and using annotation and metadata tagging tools (e.g., Dataloop AI, AWS SageMaker)
Strong communication and stakeholder management skills, with a proven ability to align cross-functional teams around data product goals Excellent organizational and prioritization skills in a fast-paced environment Domain knowledge in the financial industry is a plus Business fluency in both English and German (minimum C1 level)

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.