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experience with the Azure Fabric Stack (Microsoft Fabric, Azure Data Factory, Databricks, Azure SQL).\nMust have experience with SQL and Data Modelling in Azure / Fabric stack.\nMust have prior experience with the Property and Casualty insurance domain.\n5-8 years of hands-on data engineering experience, with strong expertise in SQL, Data Modelling, ETL/ELT, and scalable data pipeline development.\nAdvanced SQL Server/T-SQL skills, including complex query development, performance optimisation, stored procedures, and data reconciliation/validation techniques.\nHands-on proficiency in Python/PySpark for data engineering, automation, reusable data-processing solutions, and testing.\nExperience designing and implementing cloud-based data solutions, preferably using Azure technologies such as Microsoft Fabric, Azure Data Factory, Databricks, Azure SQL, and related services.\nStrong understanding of data quality, lineage, governance, monitoring, reconciliation, exception handling, and production reliability.\nStrong analytical and problem-solving skills, with the ability to investigate complex data issues, identify root causes, validate large data sets, and develop practical solutions.\nDemonstrated ability to work independently and proactively, take end-to-end ownership, drive work with limited supervision, and follow issues through to resolution.\nSelf-driven and automation-focused mindset, with a strong emphasis on engineering efficiency, repeatability, testing, maintainability, and continuous improvement.\nStrong collaboration and communication skills, with the ability to translate business and technical requirements into reliable data solutions.\nExperience supporting BI, analytics, data science, and AI-enabled workloads.\n\nPreferred / Plus: \nExperience with JSON and REST API integrations, including data ingestion, transformation, validation, error handling, and enterprise platform integration.\nHands-on experience with Azure DevOps, Git-based development, and automated CI/CD pipelines, including environment-based deployment processes across development, test, and production.\nExperience with SQL Server database projects and DACPAC build/deployment automation, including schema comparison, controlled promotion, validation, and CI/CD-based database deployments.\nProperty and Casualty insurance experience and insurance data-modelling knowledge, particularly across policy, premium, claims, exposure, finance, and reinsurance data.\nHands-on experience using Claude/Claude Code or similar AI-assisted development tools for data/software engineering, code review, testing, troubleshooting, and engineering productivity.\nExperience incorporating AI-assisted development into governed engineering workflows with appropriate code review, testing, security, and deployment controls.\nExperience with Microsoft Fabric, Databricks, Azure ML/Azure AI, and modern cloud-native data engineering practices.\nSkills\nAzure, Data Engineering, ELT, ETL, Fabric, 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