What the role is?

In this role, you will be responsible for ensuring that our data platforms, pipelines, analytics solutions, and related legacy systems are stable, scalable, secure, and aligned with business priorities.

·         Lead the end-to-end delivery, support, maintenance, and enhancement of enterprise data platforms, data pipelines, databases, dashboards, reporting solutions, and data-related legacy systems.

·         Manage the data portfolio, delivery roadmap, product backlog, priorities, resources, risks, issues, budgets, and dependencies to ensure quality delivery within agreed scope, timeline, and cost.

·         Partner with business stakeholders to understand requirements and translate business needs into scalable data solutions, data products, technical specifications, and delivery plans.

·         Define and maintain the data platform strategy, target architecture, technology roadmap, integration principles, and engineering standards.

·         Embed data governance, data quality, metadata, lineage, privacy, security, access controls, documentation, and audit requirements into platform delivery and operations.

·         Drive operational resilience through proactive monitoring, incident management, root-cause analysis, service improvement, disaster recovery readiness, and automation.

·         Lead, coach, and develop a multidisciplinary team of data professionals, while coordinating internal, offshore, and vendor resources.

·         Manage external vendors, service providers, system integrators, and technology partners to ensure deliverables meet quality, security, service, timeline, and cost expectations.

·         Promote business adoption of modern analytics, business intelligence, self-service data, automation, and AI-enabled capabilities.

Who we look for?

·         Bachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, or a related discipline.

·         Minimum 8 years of relevant experience in data engineering, enterprise data platforms, business intelligence, analytics, or data management, with proven leadership experience.

·         Strong experience in enterprise data platform delivery, production support, cloud migration, platform modernization, and data service management.

·         Solid knowledge of data architecture and the end-to-end data lifecycle, including ingestion, integration, storage, transformation, modelling, consumption, and governance.

·         Hands-on exposure to cloud data platforms, preferably Microsoft Azure, and technologies such as Databricks, Azure Data Factory, Azure SQL, Synapse Analytics, Microsoft Fabric, Power BI, Qlik Sense, SQL, Python, PySpark, ETL/ELT, data warehouses, data lakes, or Lakehouse architectures.

·         Proven ability to manage projects, vendors, budgets, service levels, incidents, risks, and competing business priorities.

·         Strong stakeholder management, communication, presentation, negotiation, analytical, and problem-solving skills.

·         Experience in the financial services or insurance industry, including relevant risk, cybersecurity, compliance, and regulatory requirements, is preferred.

·         Proficiency in written and spoken English and Chinese including Putonghua.