Insurance Data Eingeering Manager, Contract

Morgan McKinley; Hong Kong Island; On-site; HKD 1,000,000 - 1,800,000; Full time

Job summary

Morgan McKinley is seeking an experienced data engineering leader in Hong Kong to drive a team delivering end‑to‑end data solutions for insurance operations. You will oversee pipelines, real‑time data services and API integrations while hands‑on on critical components to ensure quality and scalability.

Ideal candidates bring 6–10 years in data engineering and a track record of mentoring engineers, with strong experience in Kafka, Spark, Databricks, ADF and Azure.

Qualifications

• Bachelor’s degree or higher in CS/IT/Engineering or related field.
• 6–10 years of experience in data engineering, data transformation, data integration or related roles.
• Proven insurance industry experience with operations and processes.
• Experience as a technical team leader or engineering manager.
• Hands-on data engineering with pipelines, streaming and enterprise integration.
• Practical experience with Kafka, Spark, Databricks and Azure Data Factory.
• Strong SQL, data modeling, ETL/ELT, and data quality management.
• Experience with APIs, microservices and frontend or business app integration.
• Proficiency in Python, Scala, Java or C#.
• Experience with cloud data platforms, preferably Microsoft Azure.
• Strong stakeholder management and project delivery skills.
• Ability to mentor engineers and guide architectural decisions.
• AI-ready data platform development experience is a plus.

Responsibilities

• Lead a team of data engineers with people management and day‑to‑day guidance.
• Collaborate with business, technology and data stakeholders to deliver end‑to‑end data solutions.
• Gather and analyse insurance operations requirements and translate into scalable data systems.
• Oversee design, development, testing, deployment and support of data engineering and API solutions.
• Remain hands-on in data engineering while providing technical reviews and coaching.
• Design and optimise data pipelines and real‑time services using Kafka, Spark, Databricks, ADF.
• Ensure data platforms are scalable, secure, performant, cost‑effective and maintainable.
• Manage end‑to‑end delivery including planning, risk and post‑implementation support.
• Coordinate data and API integration with frontend and business apps.
• Lead code reviews, develop standards, improve testing and deployment processes.
• Present recommendations to senior stakeholders and support project decisions.
• Contribute to AI‑ready data platform initiatives and future digital transformation.

Skills

Team leadership

Data engineering

Kafka

Spark

Databricks

Azure Data Factory

API integration

SQL

Python

Java

C#

Cloud platforms

Stakeholder management

Project management

AI-ready data platforms

Education

Bachelor’s degree in Computer Science, Information Technology, Engineering

Job description

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 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.