• 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.