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Swiss Re is a leading provider of Life and Health (L&H) reinsurance. We are looking for a Senior BI Engineer / BI Solution Architect to shape the technical direction of our Valuations & Modelling analytics landscape. You will own the end-to-end architecture of BI and analytics solutions built on Microsoft Power BI, Oracle, and Azure/Fabric services, and set the standards that our globally distributed engineering community follows.
This is a senior technical leadership role. You will act as a trusted advisor to actuarial and IT stakeholders, drive complex multi-squad initiatives, remove architectural roadblocks, and coach the next generation of BI engineers. You will balance long-term platform strategy with hands-on delivery of the most challenging technical problems.
We are a large, globally distributed team with actuarial and IT stakeholders working together in an agile development environment. We deliver solutions that calculate reserves for Swiss Re's Actuarial Reserving Unit.
Our landscape processes large volumes of data and relies on automation, coordination, visualization, control, and auditing. The systems include in-house solutions across multiple cloud platforms and integrations with industry-leading actuarial modeling software.
As a team member, you will learn how enterprise-scale analytics solutions are built, supported, and continuously improved.
We may use AI-powered tools to support the review and evaluation of applications for this position. These tools provide additional insights to our recruitment teams, but all hiring decisions are carefully reviewed and made by people. To learn more about how we use AI in recruitment and how we handle your personal data, please review our Data Privacy Statement before applying.
Swiss Reinsurance Company Ltd, commonly known as Swiss Re, is a reinsurance company based in Zurich, Switzerland. It is the world's largest reinsurer, as measured by net premiums written
Job ID: 152172193
Skills:
data discovery , Metadata Management, Kafka, Slas, Data Modeling, Python, Data Lineage, Google Cloud Platform, Sql, Query Optimization, Data Quality, Clustering, cdc, data pipelines, observability practices, dimensional models, Google BigQuery, data versioning, Pub Sub, data lakehouse principles, streaming architectures, Parquet, SCDs, AI ML use cases, SLOs, partitioning, Google Cloud Storage
Skills:
BigQuery, DataFlow, Talend, Python, Sql, ELT, Etl, Pub Sub, dbt
Skills:
Apache Airflow, Azure Data Factory, Databricks, Python, Sql
Skills:
Tableau, ELT, SQL Server, Star Schema, Typescript, Pyspark, Kafka, Spark Streaming, Power Bi, Etl, Azure Databricks, Python, MongoDB, data warehouse design, dimensional modelling, data quality frameworks, lakehouse patterns, Palantir Foundry
Skills:
BigQuery, Aws, Azure, Python