Data Engineer

Domain Knowledge (Preferred) Experience with actuarial tools or insurance is preferred. The intent is familiarity with the data terminologies and the hierarchy of data in the Insurance domain, specifically in the following areas: Familiarity with reinsurance broking data, including placements, treaty structures, client hierarchies, and renewal workflows. Understanding of actuarial rating inputs and outputs, including exposure and experience data, layers, tags, and program structures. Experience building data pipelines that support actuarial analytics, pricing tools, and downstream reporting for brokers and clients. Experience Required 10+ years of experience in implementing Microsoft BI/Azure BI solutions such as Azure Data Factory, Azure Databricks, Azure Analysis Services, SQL Server Integration Services, SQL Server Reporting Services. Strong understanding of Azure Big Data technologies like Azure Data Lake Analytics, Azure Data Lake Store, Azure Data Factory, and experience in moving data from flat files and SQL Server using U-SQL jobs. Expertise in data warehouse development from inception to implementation and ongoing support, with a strong understanding of BI application design and development principles using normalization and denormalization techniques. Experience in developing staging zones, and bronze, silver, and gold data layers. Proficiency in implementing ETL business rules between homogenous and heterogeneous systems using Azure Data Factory (ADF). Experience developing notebooks for data movement from raw to staged and curated zones using Databricks. Involvement in developing complex Azure Analysis Services tabular databases, deploying them in Azure, and scheduling cubes via Azure Automation Runbook. Extensive experience in developing and deploying SSAS cubes (tabular and multidimensional), including KPIs, measures, partitioning, data mining models, and processing. #J-18808-Ljbffr