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Manulife Financial

Global financial services: insurance and investments

Lead Data Solution Architect

Data EngineeringPosted on Nov 13
Full-timeHong KongNo salary listed

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline.
  • At least 10 years of experience in data architecture, solution architecture, data engineering, or enterprise data platforms, including designing enterprise data lakes, lakehouse platforms, and scalable cloud data solutions, with accountability for complex design decisions.
  • Strong hands-on experience with Azure Databricks, including Unity Catalog, Spark/PySpark, Python, SQL, Azure Data Factory, and Azure Data Lake Storage.
  • Experience with batch and streaming pipelines, ETL/ELT, APIs and cloud integration, reporting, analytics, and data products.
  • Experience designing multi-country data platforms under data residency and privacy constraints, including RBAC models and least-privilege access across data products.
  • Experience with DevSecOps, CI/CD, cloud security, data protection, monitoring, and operational resilience.
  • Ability to lead design discussions, resolve complex issues, and influence senior business and technology stakeholders.
  • Strong communication and prioritisation skills in a fast-changing environment.
  • Excellent written and spoken English.

Responsibilities

  • Own the development and maintenance of the GWAM Asia data architecture roadmap, aligned with GWAM Asia priorities and enterprise technology strategy.
  • Architect scalable end-to-end solutions across integration, ingestion, curation, storage, common data models, semantic layers, reporting, analytics, GenAI, and business-facing data products.
  • Translate business objectives into target-state architectures, solution options, data requirements, integration patterns, and phased roadmaps.
  • Lead design reviews, provide technical sign-off, and guide cross-functional delivery teams in Manila and Chengdu.
  • Define standards for data pipelines, lakehouse design, APIs, DevSecOps, observability, security, resilience, and operational support.
  • Ensure enterprise and canonical data models designed with the Data Modeller fit the target architecture, and design Unity Catalog and role-based access control models that enforce least-privilege access.
  • Ensure compliance with enterprise architecture, data governance, cybersecurity, risk, audit, and application performance standards.
  • Maintain architecture artefacts and decision records, drive continuous improvement, and conduct focused proofs of concept for emerging technologies.

Desired Qualifications

  • Experience in financial services, wealth management, insurance, or asset management across Asia markets.
  • Practical experience with Azure OpenAI and GenAI patterns, including prompt engineering, retrieval-augmented generation, vectorisation, and similarity search.
  • Experience with Databricks SQL Warehouse, Microsoft Fabric/Power BI, and Azure Kubernetes Service.
  • Knowledge of data governance, metadata, master and reference data, data quality, lineage, data contracts, and control frameworks.
  • Experience with data products, MLOps, event-driven patterns, Change Data Capture, or containerised architectures.
  • Relevant Azure, Databricks, data architecture, GenAI, or Azure AI certifications.
  • Spoken Mandarin.

About the Company

Manulife Financial

Global financial services: insurance and investments

Manulife Financial is a global financial services provider offering a wide range of insurance and investment solutions. It serves individuals, businesses, and institutions with products such as life and health insurance, wealth management, and retirement plans. Customers fund these products through premiums, fees for asset management, and investment income earned on invested assets. Manulife uses analytics and technology to tailor services and improve efficiency, aiming to help clients protect their finances, grow their wealth, and plan for retirement. The company differentiates itself through its large international presence in North America, Asia, and Europe, its breadth of products, and its emphasis on data-driven insights to personalize offerings. Its goal is to help customers achieve their financial goals and aspirations by providing comprehensive, paid-for financial solutions and ongoing support across multiple regions.

Company size
10,001+
Company stage
IPO
Headquarters
Toronto, Canada
Founded
1887

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