ResponsibilitiesLead the design and development of scalable, secure, and high-performance data architecture solutions to support enterprise-wide data transformation initiatives.Ensure compliance with Hong Kong’s regulatory frameworks, including the PDPO and GDPR, while aligning with the organization’s strategic business goals.Collaborate with the Group Data Centre of Excellence (CoE) to implement data strategies that adhere to group-wide standards and address local business requirements.Partner with data modellers to create data models that meet business needs, incorporating domain expertise in Hong Kong’s Life and General Insurance sectors to reflect industry and regulatory standards.Oversee data integration strategies, including ETL/ELT processes across legacy systems, cloud platforms, and third-party solutions.Define and enforce data architecture standards, development guidelines, and best practices to ensure consistency, quality, and scalability.Work closely with data engineers, analysts, and business stakeholders to gather requirements and deliver tailored data solutions.Maintain comprehensive documentation of data flows, architecture diagrams, and metadata repositories to support governance, compliance, and operational transparency.RequirementsBachelor’s degree in Computer Science, Information Technology, or a related discipline.Minimum of 8 years’ experience in data architecture and database design, ideally within the insurance industry (e.g., policy, claims, underwriting, actuarial, or regulatory reporting).Proven expertise in designing data solutions on Microsoft Azure, with hands-on experience using Azure Databricks to process, transform, and analyze structured, semi-structured (e.g., JSON, XML), and unstructured (e.g., text, images) insurance data.Skilled in orchestrating complex ETL/ELT pipelines using Azure Data Factory, handling diverse data formats across large, heterogeneous insurance datasets.Extensive experience with Azure Data Lake Storage Gen2 for scalable storage and retrieval of various insurance data types.Strong background in designing data models and schemas for analytics, machine learning, and regulatory reporting within Databricks environments.Proficient in automating and deploying Databricks solutions using GitHub Actions and CI/CD practices.Deep understanding of data security principles, including RBAC, managed identities, encryption, and privacy regulations such as GDPR and insurance-specific compliance.Hands-on experience with Informatica for metadata management, data lineage, cataloguing, and governance in regulated environments.Ability to translate complex insurance business requirements into scalable, production-ready data architectures on Azure and Databricks.All applications applied through our system will be delivered directly to the advertiser and privacy of personal data of the applicant will be ensured with security.