Insurance Data Eingeering Manager, Contract

Morgan Mckinley Limited; Hong Kong; On-site; HKD 900,000 - 1,300,000; Full time

Job summary

Morgan McKinley Limited is seeking a seasoned Data Engineering Lead in Hong Kong to coach a team, shape data architecture, and deliver end-to-end data pipelines for insurance operations.

You will stay hands-on with implementation details while guiding design reviews, standards, and best practices. Experience with Kafka/Spark/Databricks and cloud data platforms is essential to drive scalable AI-ready data solutions.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering or a related discipline.
• 6-10 years of relevant experience in data engineering, data transformation, data integration or related technology roles.
• Proven experience in the insurance industry, particularly with insurance operations, processes and business requirements.
• Previous experience as a technical team leader or engineering manager.
• Strong hands-on experience in data engineering, data pipelines, real-time data streaming and enterprise system integration.

Responsibilities

• Lead a team of data engineers, providing people management, technical guidance, coaching and day-to-day support.
• Work closely with business, technology and data stakeholders to deliver end-to-end data engineering solutions.
• Gather and analyse business requirements with a focus on insurance operations and translate them into scalable data solutions.
• Lead design, development, testing, implementation and support of data engineering, data transformation, streaming and API solutions.
• Remain hands-on in data engineering and transformation activities while providing technical advice and reviewing engineering deliverables.
• Design and optimise data pipelines and real-time data services using Kafka, Spark, Databricks, Azure Data Factory and EFL.
• Ensure quality, scalability, security, performance, cost efficiency and maintainability of data platforms.
• Manage end-to-end delivery including project planning, design, resource coordination, risk management, testing and deployment.
• Collaborate with frontend and application teams to support data and API integration with business applications.
• Lead code reviews, establish development standards, improve testing and deployment processes, and promote reusable practices.
• Present technical recommendations to senior stakeholders and support decision-making across projects.
• Contribute to development of an AI-ready data platform and future data/digital transformation initiatives.

Skills

People management

Technical guidance

Stakeholder management

Project management

SQL

Programming (Python/Scala/Java/C#)

Cloud data platforms

Education

Bachelor's degree in Computer Science/IT/Engineering

Tools

Kafka

Spark

Databricks

Azure Data Factory

Job description

Lead a team of data engineers, providing people management, technical guidance, coaching and day-to-day support.

Work closely with business, technology and data stakeholders to deliver end-to-end data engineering solutions.

Gather and analyse business requirements, with a focus on insurance operations and business processes, and translate them into scalable data solutions.

Lead the design, development, testing, implementation and support of data engineering, data transformation, streaming and API solutions.

Remain hands-on in data engineering and transformation activities while providing technical advice and reviewing engineering deliverables.

Design and optimise data pipelines and real-time data services using technologies such as Kafka, Spark, Databricks, Azure Data Factory and EFL.

Ensure the quality, scalability, security, performance, cost efficiency and maintainability of data platforms and solutions.

Manage end-to-end delivery, including project planning, technical design, resource coordination, risk management, testing, deployment and post-implementation support.

Collaborate with frontend and application teams to support data and API integration with business applications.

Lead code reviews, establish development standards, improve testing and deployment processes, and promote reusable engineering practices.

Present technical recommendations to senior stakeholders and support decision-making across projects.

Contribute to the development of an AI-ready data platform and support future data, analytics and digital transformation initiatives.

Requirements

Bachelor's degree in Computer Science, Information Technology, Engineering or a related discipline.

6-10 years of relevant experience in data engineering, data transformation, data integration or related technology roles.

Proven experience in the insurance industry, particularly with insurance operations, processes and business requirements.

Previous experience as a technical team leader or engineering manager.

Strong hands-on experience in data engineering, data pipelines, real-time data streaming and enterprise system integration.

Practical experience with EFL, Apache Kafka, Apache Spark, Databricks and Azure Data Factory.

Experience delivering data engineering projects from requirements gathering and solution design through development, testing, deployment and support.

Strong understanding of databases, SQL, data modelling, ETL/ELT processes and data quality management.

Experience with APIs, microservices and frontend or business application integration.

Proficiency in one or more programming languages, such as Python, Scala, Java or C#.

Experience working with cloud data platforms, preferably Microsoft Azure and Azure data services.

Strong stakeholder management, communication, problem-solving and project management skills.

Ability to provide practical technical advice, mentor engineers and make sound architectural and delivery decisions.

Experience transforming existing data platforms into AI-ready environments would be an advantage.