Azure Data Engineer

Job Title

Design, build, and maintain scalable and efficient ETL/ELT pipelines in Azure Databricks to process structured, semi-structured, and unstructured insurance data from multiple internal and external sources. • Collaborate with data architects, modellers, analysts, and business stakeholders to gather data requirements and deliver fit-for-purpose data assets that support analytics, regulatory, and operational needs. • Develop, test, and optimize data transformation routines, batch and streaming solutions (leveraging tools such as Azure Data Factory, Data Lake Storage Gen2, Azure Event Hubs, and Kafka) to ensure timely and accurate data delivery. • Implement rigorous data quality, validation, and cleansing procedureswith a focus on enhancing reliability for high-stakes insurance use cases, reporting, and regulatory outputs. • Integrate Informatica tools to facilitate data governance, including the capture of data lineage, metadata, and data cataloguing as required by regulatory and business frameworks. • Ensure robust data security by following best practices for RBAC, managed identities, encryption, and compliance with Hong Kong's PDPO, GDPR, and other relevant regulatory requirements. • Automate and maintain deployment pipelines using GitHub Actions to ensure efficient, repeatable, and auditable data workflows and code releases. • Conduct root cause analysis, troubleshoot pipeline failures, and proactively identify and resolve data quality or performance issues. • Produce and maintain comprehensive technical documentation for pipelines, transformation rules, and operational procedures to ensure transparency, reuse, and compliance. • Apply subject matter expertise in Hong Kong Life and General Insurance to ensure that development captures local business needs and industry-specific standards.