Azure Fabric Data Engineer

Requirements:

• Minimum 5 years of Hands-on development in Azure Data Engineering
• Minimum 5 years of Hands-on experience in Python, Spark and SQL Development.
• Should have hands-on experience with the Azure Fabric Stack (Microsoft Fabric, Azure Data Factory, Databricks, Azure SQL).
• Must have experience with SQL and Data Modelling in Azure / Fabric stack.
• Must have prior experience with the Property and Casualty insurance domain.
• 5-8 years of hands-on data engineering experience, with strong expertise in SQL, Data Modelling, ETL/ELT, and scalable data pipeline development.
• Advanced SQL Server/T-SQL skills, including complex query development, performance optimisation, stored procedures, and data reconciliation/validation techniques.
• Hands-on proficiency in Python/PySpark for data engineering, automation, reusable data-processing solutions, and testing.
• Experience designing and implementing cloud-based data solutions, preferably using Azure technologies such as Microsoft Fabric, Azure Data Factory, Databricks, Azure SQL, and related services.
• Strong understanding of data quality, lineage, governance, monitoring, reconciliation, exception handling, and production reliability.
• Strong analytical and problem-solving skills, with the ability to investigate complex data issues, identify root causes, validate large data sets, and develop practical solutions.
• Demonstrated ability to work independently and proactively, take end-to-end ownership, drive work with limited supervision, and follow issues through to resolution.
• Self-driven and automation-focused mindset, with a strong emphasis on engineering efficiency, repeatability, testing, maintainability, and continuous improvement.
• Strong collaboration and communication skills, with the ability to translate business and technical requirements into reliable data solutions.
• Experience supporting BI, analytics, data science, and AI-enabled workloads.

Preferred / Plus:

• Experience with JSON and REST API integrations, including data ingestion, transformation, validation, error handling, and enterprise platform integration.
• Hands-on experience with Azure DevOps, Git-based development, and automated CI/CD pipelines, including environment-based deployment processes across development, test, and production.
• Experience with SQL Server database projects and DACPAC build/deployment automation, including schema comparison, controlled promotion, validation, and CI/CD-based database deployments.
• Property and Casualty insurance experience and insurance data-modelling knowledge, particularly across policy, premium, claims, exposure, finance, and reinsurance data.
• Hands-on experience using Claude/Claude Code or similar AI-assisted development tools for data/software engineering, code review, testing, troubleshooting, and engineering productivity.
• Experience incorporating AI-assisted development into governed engineering workflows with appropriate code review, testing, security, and deployment controls.
• Experience with Microsoft Fabric, Databricks, Azure ML/Azure AI, and modern cloud-native data engineering practices.