1.1.1 Overview:
We are seeking a Senior Health Data Engineer to drive the design and implementation of a common Health Data Model and Health Data Products to provide ready-to-use, easily consumable, trusted data set to support the AI and analytics use cases required to drive Manulife’s Health business ambition. This role is critical in enabling business units to innovate faster, optimize operations, and deliver localized analytics and AI capabilities. The successful candidate will participate in regional health strategic initiatives such as Provider Management Solutions, Health KPIs and Claim Driver analyses/automation, and other Regional/Local Health Analytics/AI use cases that require a common health data model.
As part of ADO, you will have the opportunity to:
Lead regional health data initiatives impacting regional and local health businesses
Collaborate with data scientists, AI teams, and business leaders in a dynamic, forward-thinking environment.
Drive innovation and shape the future of health data products within the organization, to enable cutting-edge analytics/AI use cases including Generative AI (GenAI) , Large Language Models (LLMs) , Agentic AI , and advanced solutions leveraging OpenAI GPT models and AliCloud Qwen models .
1.1.2 Key Responsibilities:
1.1.2.1 Lead Health Data Engineering Design and Delivery Partner with the regional and local health business teams, local data offices, AI/Analytics team, and cross-functional technical teams to design, build, and deploy an Asia regional common health data model, leveraging existing ADO platform, governance, practices and standards.
Define engineering standards and enforce best practices for scalability, performance, and reliability.
Oversee end-to-end engineering delivery from concept to production, including testing, deployment, and monitoring.
Establish robust frameworks, pipelines, and reusable components to develop a common data model across business units, to enable reusability and ready-to-consume data sets.
1.1.2.2 Technical Leadership and Troubleshooting Provide hands-on technical leadership during implementation phases, guiding engineering teams through complex challenges.
Act as the primary escalation point for engineering issues across multiple projects.
Conduct code reviews, performance tuning, and optimization to ensure high-quality, secure deployments.
1.1.2.3 Compliance, Security, and Risk Management Integrate compliance and security controls into the common Health data model and data products, ensuring adherence to regulatory requirements and internal governance standards.
Proactively identify risks related to model deployment, data privacy, and ethical considerations, and implement mitigation strategies.
Maintain documentation and audit trails for all Health Data Engineering activities.
1.1.2.4 Community of Practice Contribution Actively contribute to the Data Engineering Community of Practice by sharing best practices, reusable assets, and technical insights.
Foster collaboration and knowledge exchange across regions to accelerate Health data product maturity within the organization.
1.1.3 Qualifications & Skills:
Education: Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
Experience: 10+ years in one or more of the following Data Engineer
Platform Engineer
DevOps Engineer
Software Engineer
Technical Expertise:
o Proficient understanding of distributed computing principles
o Good Knowledge of Hadoop cluster, Azure, with all included services
o Ability to solve any ongoing issues with operating the cluster
o Experience with Azure ADLS, Data Factory, Databricks, Event Hubs
o Experience with data engineering projects
i.e. integration of data from multiple data sources to a target system
o Good knowledge of data querying tools – Azure Synapse Analytics, Databricks SQL Warehouse
o Knowledge in data streaming (e.g. Event Hubs, Spark)
o Knowledge in Python and Spark
o…