20 hours ago
Chengdu, ChinaSenior
Responsibilities
- Design and build data products and contribute to the overall data product strategy.
- Design and maintain conceptual, logical, physical, and dimensional data models.
- Integrate multiple source systems into enterprise data platforms and data products.
- Develop and support enterprise-scale data pipelines and ETL/ELT integrations using Azure Data Factory, Databricks, Synapse, Spark, Python, and SQL.
- Maintain and support the Enterprise Data Lake, including platform monitoring, reliability, performance optimization, incident investigation, and continuous improvement.
- Conduct proof-of-concepts for new integration patterns, technologies, and data solutions.
- Create technical documentation, design specifications, and operational runbooks.
- Perform unit testing, system integration testing, and deployment validation.
- Support Agile delivery teams across design, development, testing, deployment, and production support.
- Collaborate with business, technology, and data stakeholders across Asia and Canada.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline.
- 10+ years of experience in Data Engineering, Data Platform Engineering, DevOps Engineering, or related technical roles.
- Strong hands-on experience with Azure Data Platform technologies, including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage, Event Hubs, Spark/PySpark, Python, SQL, and Databricks SQL Warehouse.
- Experience with database development and management, including technologies such as Azure SQL and Cosmos DB.
- Strong enterprise-scale data modeling experience covering conceptual, logical, physical, and dimensional models.
- Experience designing scalable cloud-based data solutions and enterprise data platforms.
- Experience with Change Data Capture technologies such as Debezium, streaming technologies, and enterprise data lake architectures.
- Strong analytical, problem-solving, and troubleshooting skills, plus experience working in Agile delivery teams.
- Preferred experience in financial services, wealth management, insurance, or asset management.
- Preferred knowledge of data governance, master data management, metadata management, and data quality frameworks.
- Preferred understanding of data product concepts, including data domains, reusable data assets, data ownership, data contracts, and business-facing data consumption.
- Preferred experience with AI, Business Intelligence, and/or Generative AI solutions and global distributed teams.
- Excellent written and spoken English is mandatory, with strong communication, collaboration, and stakeholder management skills.
Benefits
- Hybrid working arrangement.
- Flexible environment supporting learning, career growth, well-being, and inclusion.
- Global team environment with opportunities to work across Asia and Canada.
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.