The Risk Intelligence and Knowledge Systems (RIKS) unit is part of the Life &
Health division, serving as a regional analytics centre for Europe, UK, and
Latin Americas. The overall department is responsible for AI strategy
development and execution, biometrics insights, and knowledge modelling for more
than 40 markets, 500+ cedents, and 1,500+ active reinsurance contracts. We
strategically invest in scalable, easy-to-use data and knowledge technologies to
create and operationalize high-quality products and services using structured
and unstructured data, serving both internal and external clients. We believe
that better data and advanced analytics can strengthen our reinsurance core and
will be the foundation for the business models of tomorrow.

Do you sit at the intersection of actuarial thinking and data engineering? Do
you understand what seriatim data is, why portfolio preparation matters, and how
to turn messy cedent data deliveries into reliable, analytics-ready assets? We
are looking for a motivated individual to join RIKS as a Data Engineer, based in
Madrid.



You will own the preparation, engineering, and quality assurance of Life
& Health reinsurance data – from raw cedent input to structured portfolio –
supporting business transformation of pricing, underwriting, experience studies,
and valuation functions across our regional markets.

Your Job

* Receive, validate, and prepare cedent data deliveries (seriatim and
summarised portfolio data as an example), applying domain knowledge to assess
completeness, plausibility, and fitness for downstream analysis
* Design and implement ETL/ELT pipelines that automate the ingestion,
transformation, and loading of recurring and ad-hoc data deliveries into our
data platform
* Prepare and structure portfolio datasets for consumption by pricing,
underwriting, claims, experience studies, and valuation teams; ensure data is
accurate, well-documented, and traceable
* Build and maintain data infrastructure on Azure and Data

📌 Data Engineer (Madrid)
🏢 Munich Re Careers
📍 Madrid