1) Overview 

A Hong Kong Insurance Company is seeking a seasoned and exceptionally skilled Data Solution Lead to join our Digital Delivery team. This pivotal role leverages advanced data architecture, engineering, and data strategy to drive business transformation, improving decision-making processes and focusing on Data Hub projects. The Data Solution Lead will manage the entire data lifecycle, ensuring seamless data integration and transformation from source to consumption. This individual will ensure actionable insights align with business needs, effectively functioning as a shadow PO with deep technical knowledge. The ideal candidate will possess extensive expertise in data architecture, data strategy, AWS data lakes, and platform engineering. They should challenge and guide internal IT and data teams, outmatching them in providing top-notch solutions. 

2) General Responsibilities 

a) AWS Data Platform Engineering: 

• Data Integration and Quality: Identify, integrate, and manage data from multiple sources within AWS environments (e.g., Redshift, S3, SageMaker) ensuring high data quality and governance. 

• Data Engineering: Implement robust data engineering practices using AWS tools like AWS Glue, AWS Lake Formation, ensuring data pipelines are optimized and scalable. 

• Data Lake Tagging and Management: Execute efficient data tagging strategies and governance using AWS Lake Formation to categorize, manage, and secure data within the data lake. 

b) Data Strategy and Lifecycle Management: 

• Data Strategy Formulation: Define and execute a comprehensive data strategy encompassing the entire data lifecycle, from sourcing to storage, processing, and analysis within the AWS ecosystem. 

• Lifecycle Management: Design and execute end-to-end data lifecycle processes, ensuring smooth transitions from source to landing, landing to raw, raw to curated, and curated to application zones. 

• Governance and Compliance: Enforce data governance policies and compliance standards to manage data quality, access, and usage effectively. 

c) Solution Design and Architecture: 

• Data Architecture: Design, implement, and maintain scalable and robust data architectures using AWS services. Ensure architectures are optimized for performance, cost, and scalability. 

• Data Pipeline Orchestration: Develop and manage complex data pipelines using AWS Step Functions, AWS Lambda, ensuring high availability and efficiency. 

• Infrastructure Management: Maintain and optimize the data infrastructure, leveraging AWS services to create a resilient and secure data environment. 

• Data Modeling: Design and implement comprehensive data models that support scalable and efficient data processing and analytics. 

d) Business Analysis and Solution Evaluation: 

• Requirement Gathering and User Journeys: Conduct thorough capture of end-to-end user requirements, define detailed user journeys, and translate these into technical specifications. 

• Challenging Solutions: Critically evaluate and challenge proposed solutions from vendors and internal IT teams, ensuring they meet the highest standards of efficiency, scalability, and alignment with business objectives. 

• Solution Optimization: Conduct cost-benefit analysis and feasibility studies, validating proposed solutions through PoCs and ensuring alignment with best practices and industry standards. 

• Stakeholder Communication: Engage with stakeholders to translate data requirements and solutions into actionable business insights, ensuring clear communication between technical and business teams. 

3) Skills and Qualifications 

a) Technical Skills: 

• AWS Expertise: Exceptional proficiency with AWS platforms and services, including Redshift, S3, SageMaker, Glue, Lake Formation. 

• Data Lifecycle Expertise: Deep understanding of data lifecycle processes, including efficient movement and management of data from source to landing, landing to raw, raw to curated, and curated to application zones. 

• Data Engineering Tools: Advanced knowledge of data engineering tools and techniques within the AWS ecosystem. 

• Data Management: Expertise in SQL, NoSQL databases, and big data technologies like Apache Hadoop, Spark. 

b) Data Strategy and Lifecycle: 

• Demonstrated ability to define and execute a comprehensive data strategy. 

• Proven experience in designing and managing data lifecycles within AWS environments, ensuring efficiency and scalability. 

• Strong knowledge of data governance principles and practices. 

c) Solution Design and Architecture: 

• Extensive experience in designing scalable data architectures and managing data pipeline orchestration within the AWS ecosystem. 

• High proficiency in developing complex data models and maintaining data infrastructure. 

• Ability to critically evaluate and improve proposed data solutions. 

d) Business Analysis and Leadership: 

• Expertise in gathering detailed user requirements, mapping user journeys, and challenging proposed solutions. 

• Strong stakeholder engagement capabilities, translating technical solutions into business insights. 

4. Experience 

• Education: Bachelor's Degree in Data Science, Statistics, Computer Science, or related field. Master’s or PhD preferred. 

• Experience: Minimum 7 years in data architecture, data engineering, and data strategy within AWS environments, preferably in insurance or tech-centric sectors. 

• Industry Background: Ideal candidates will have backgrounds in tech giants (e.g., AWS, Google, Microsoft), leading financial institutions (e.g., Goldman Sachs, JP Morgan), or top consulting firms (e.g., McKinsey, Deloitte) specializing in data transformation projects. 

5. Soft Skills 

• Analytical Thinking: Exceptional problem-solving skills and attention to detail. 

• Communication: Excellent communication skills, capable of explaining complex concepts clearly to varied audiences. 

• Innovation: Proactive approach to learning and applying new technologies and methodologies. 

We offer 5-day work, attractive salary, MPF, group life and group medical insurance; and excellent career development opportunities to the right candidate.

We are an equal opportunity employer and welcome applications from all qualified candidates. Application forms and resume will be kept for a period of 24 months after completion of the recruitment process. (All information will be held in strict confidence and only be used for recruitment purpose).