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# Data Engineer

- **Company:** Community Of
- **Location:** Madrid, Spain
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Microsoft Azure, Biometrics, Data Dictionary, Information Engineering, Extract Transform Load (ETL), Data Structures, R (Programming Language), Python (Programming Language), Knowledge-Based Systems, Power BI, SQL Databases, Unstructured Data, Azure Data Factory, Data Lakes, Information Technology, Data Management, Azure Synapse Analytics, Data Pipelines, Databricks
- **Published:** August 11, 2026
- **Apply:** https://es.trabajo.org/oferta-4112-eda36d4589e0101134234ac86518d5b4

## About the Role

actuarial sciences, or a comparable quantitative discipline Hands-on experience in data engineering: building ETL/ELT pipelines, working with large structured datasets, and delivering production-quality data outputs Proficient in R as a primary language (with transition path towards Python) and SQL; experience with Databricks is an advantage Experience with Azure data services (Azure Data Factory, Data Lake, Synapse, or comparable) is a plus Strong analytical mindset, comfortable performing exploratory data analysis and communicating data quality findings to non-technical audiences Practical experience with reporting or BI tools (Power BI, R Shiny, or similar) is welcome Structured, rigorous, and delivery-focused. You understand that data quality in reinsurance has real downstream consequences Comfortable working in distributed, international teams; able to engage directly with cedents and internal clients on data matters Fluent in English (written and spoken); Spanish and/or

## Description

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 Databricks,
including pipelines, data models, and orchestration workflows supporting actuarial and analytics workloads Perform exploratory data analysis on incoming data to detect anomalies, outliers, and quality issues; communicate findings clearly to business stakeholders Contribute to automation and standardization of data preparation workflows, reducing manual effort and turnaround time for cedent onboarding and data refresh cycles Collaborate with actuaries, underwriters, and data scientists to understand data requirements and translate them into robust, reusable engineering solutions Take ownership of data stewardship for the portfolio data domain: quality standards, data dictionaries, lineage documentation, and archiving Your Profile Solid understanding of Life & Health reinsurance data, familiarity with seriatim data structures, portfolio preparation, and the reinsurance functions that consume them (pricing, experience studies, valuation, claims) Background in informatics, engineering, or


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