Experteer Overview
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As a Data Engineer in Munich Re's RIKS unit in Madrid, you will own the preparation, engineering, and QA of Life & Health reinsurance data from raw cedent inputs to structured portfolios. You will design ETL/ELT pipelines and build data infrastructure on Azure and Databricks to support pricing, underwriting, experience studies, and valuation. You’ll drive data quality and documentation while collaborating with actuaries, underwriters, and data scientists to enable scalable analytics. This role offers impact across regional markets and a chance to shape data-driven insurance solutions.
Compensaciones / Beneficios
• Receive, validate, and prepare cedent data deliveries, assessing completeness and fitness for downstream analysis
• Design and implement ETL/ELT pipelines to ingest, transform, and load data into the data platform
• Prepare and structure portfolio datasets for multiple business domains (pricing, underwriting, claims, valuation)
• Build and maintain data infrastructure on Azure and Databricks with pipelines, models, and orchestration
• Perform exploratory data analysis to detect anomalies and communicate quality findings to stakeholders
• Automate and standardize data preparation workflows to reduce manual effort and onboarding time
• Collaborate with actuaries, underwriters, and data scientists to translate requirements into robust engineering solutions
• Own data stewardship for portfolio data: quality standards, dictionaries, lineage, and archiving
Responsabilidades
• Solid understanding of Life & Health reinsurance data and seriatim/portfolio structures
• Background in informatics, engineering, actuarial sciences, or quantitative discipline
• Hands-on data engineering experience with large structured datasets and production outputs
• Proficiency in SQL; R as primary xpzdshu language with Python as transition path
• Experience with Databricks is an advantage
• Experience with Azure data services (Data Factory, Data Lake, Synapse) is a plus
• Strong analytical mindset and ability to communicate data quality to non-technical audiences
• Structured, rigorous, delivery-focused approach
• Fluent in English; Spanish and/or German a plus
• Comfortable working in distributed, international teams
Requisitos principales
• Diversity, Equity & Inclusion
• Continuous Learning
• Career Mobility
• Competitive salary
• Retirement provision
• Work-life balance