Data Business Analyst

Data Business Analyst

Responsibilities:

• Gather and analyse business requirements related to data initiatives that support the enterprise-wide data transformation program.
• Translate business needs into clear data specifications, including KPIs, metrics, and reporting requirements.
• Perform data validation to ensure accuracy, consistency, and integrity as part of the enterprise-wide data transformation initiative.
• Develop and maintain dashboards, reports, and visualizations using tools such as Power BI to support ongoing data quality monitoring and identify opportunities for continuous improvement.
• Maintain and enhance data dictionaries, business processes, data flows, and business requirements to ensure transparency, traceability, and alignment across teams.
• Apply domain expertise in both Hong Kong Life and General Insurance to ensure that industry-specific requirements are accurately captured and aligned with local regulatory standards.
• Support project scrum execution by actively participating in sprint planning, daily stand-ups, and retrospectives, ensuring data-related tasks are clearly defined, prioritized, and delivered on time.

Experience Required:

• Bachelor's degree in Business Analytics, Information Systems, Computer Science, Statistics, Actuarial Science, or a related field.
• 3+ years of experience as a data/business analyst working within insurance or financial services, with exposure to policy, claims, customer, or risk data.
• Strong skills in data querying, profiling, and transformation using SQL and Spark (Databricks/Spark SQL).
• Experience translating business requirements into data requirements, mapping data flows, and defining user stories/specs for data engineering teams.
• Familiarity with data governance platforms and best practices, especially using Informatica for data cataloguing, metadata management, and lineage.
• Understanding of insurance industry standards and regulatory requirements as they impact data capture, usage, and reporting (e.g., IFRS 17, Solvency II).
• Experience documenting data models, dictionaries, and business glossaries, and supporting user acceptance testing for analytical or reporting solutions.
• Excellent communication skills to work cross-functionally with business stakeholders, data engineers, architects, and governance teams.