3 months ago
Hong Kong, Hong KongSenior
Responsibilities
- Partner with business leaders, product owners, and IT stakeholders to capture requirements, define project scope, and establish delivery timelines.
- Estimate workload and effort and decompose complex data initiatives into technical epics, user stories, and execution roadmaps.
- Drive delivery from architecture design through testing, deployment, and operational handoff while managing risks, dependencies, and scope creep.
- Design, build, and optimize batch and real-time data pipelines, data lakehouse architectures, and data warehousing solutions.
- Provide technical leadership for enterprise data platforms, architecture, engineering practices, platform optimization, and innovation.
- Implement data orchestration, ingestion, cleansing, transformation, augmentation, and data quality processes.
- Establish technical quality standards, data governance frameworks, and best practices for data ingestion, storage, and processing.
- Conduct code reviews, lead technical troubleshooting, and ensure pipelines are secure, resilient, and cost-optimized.
- Mentor and coach mid-level and junior data engineers.
Requirements
- Bachelor’s or master’s degree in Computer Science, Information Systems, Quantitative Engineering, or a related field.
- Minimum 10+ years of IT experience, including at least 3+ years in data engineering delivery leadership or technical lead roles.
- Strong understanding of insurance or financial services domains, such as policy administration, claims management, actuarial metrics, or agency analytics.
- Proven delivery leadership experience in effort estimation, scope decomposition, sprint planning, and cross-functional stakeholder management.
- Hands-on experience with Azure Cloud Services, Azure Data Lake Storage, Azure Data Factory, Azure SQL or Synapse, and database technologies such as Oracle, SQL Server, or PostgreSQL.
- Strong proficiency with Azure Databricks, Apache Spark, PySpark, Spark SQL, and modern ETL/ELT pipeline design.
- Deep expertise in enterprise data design, Kimball dimensional modeling, data lakehouse architecture, and data warehousing.
- Strong verbal and written communication skills for explaining technical visions, architectural trade-offs, and project updates to non-technical stakeholders.
- Practical experience or familiarity with AliCloud DataWorks, MaxCompute, OSS, and Hologres.
- Experience with FineBI, Power BI, or similar enterprise reporting tools.
Benefits
- Flexible environment supporting learning, career growth, well-being, and inclusion.
- Global team environment with support for shaping career development.
- Hybrid working arrangement.
Tech Stack
Categories
Data Engineering
About Manulife
Manulife is a Toronto‑headquartered public financial services company that provides life and health insurance, retirement plans, and wealth and asset management to individuals and institutions. It earns premiums and fee income from insurance, investment, and advisory products delivered across Canada, Asia, and Europe, and operates as John Hancock in the United States. Founded in 1887, the company is listed on the Toronto Stock Exchange.