Senior Azure Data Engineer – Insurance/Reinsurance Analytics

Job Summary

About the role

The ideal candidate will be well-versed in Microsoft Azure data services and have a working knowledge of insurance or actuarial data, particularly in the reinsurance and analytics space.

Responsibilities

• Drive end-to-end data solutions from ingestion to insights
• Collaborate in an Agile team environment
• Implement Microsoft BI/Azure BI solutions including ADF, Databricks, SSAS, SSIS, and SSRS
• Develop data warehouse development from inception to deployment, using normalization and denormalization techniques
• Develop data lake layers (staging, bronze, silver, gold) for structured and unstructured data ingestion and curation
• Develop notebooks in Databricks to support ETL workflows and data transformation
• Build and deploy Azure Analysis Services tabular models and automate scheduling using Azure Automation Runbooks
• Develop SSAS cubes (tabular and multidimensional), aggregations, KPIs, partitions, and data mining models

Requirements

• Proven experience in implementing Microsoft BI/Azure BI solutions including ADF, Databricks, SSAS, SSIS, and SSRS
• Strong understanding of Azure Big Data technologies (ADLS, ADF, Data Lake Analytics) and data movement using U-SQL jobs
• Expertise in data warehouse development from inception to deployment, using normalization and denormalization techniques
• Experience developing data lake layers (staging, bronze, silver, gold) for structured and unstructured data ingestion and curation
• Skilled in developing notebooks in Databricks to support ETL workflows and data transformation
• Experienced in building and deploying Azure Analysis Services tabular models and automating scheduling using Azure Automation Runbooks
• Deep knowledge in developing SSAS cubes (tabular and multidimensional), aggregations, KPIs, partitions, and data mining models

Qualifications

• Familiarity with reinsurance broking data including placements, treaty structures, client hierarchies, and renewals
• Understanding of actuarial rating data inputs and outputs—exposures, experience data, layers, and tagging structures
• Experience building data pipelines that support actuarial models, pricing tools, and client-facing reporting

Skills

• Business Intelligence & Big Data: Azure Data Factory (ADF), Azure Databricks, Azure Analysis Services (SSAS), Azure Data Lake Analytics, Azure Data Lake Store (ADLS), Azure Integration Runtime, Azure Event Hubs, Azure Stream Analytics, DBT (Data Build Tool)
• Databases: Azure SQL, MongoDB, PySpark

Benefits

Hybrid – 3 Days Onsite Per Week

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