Your new company

Your new role

• Lead one of the data engineering squads, providing technical guidance, mentoring, and support to team members while remaining actively involved in solution delivery.
• Design, develop, and maintain robust data processing pipelines and end-to-end ETL/ELT workflows.
• Build and optimize scalable data platforms capable of processing and analysing large volumes of structured and unstructured data securely and efficiently.
• Develop, maintain, and enhance enterprise data platforms to support business intelligence, analytics, reporting, and future AI initiatives.
• Drive the design and implementation of data integration frameworks within complex enterprise application environments.
• Integrate and manage data flows across enterprise applications, databases, cloud platforms, APIs, and third-party systems.
• Support the implementation and optimisation of Data Lake, Data Warehouse, and Lakehouse architectures.
• Contribute to data platform architecture decisions, technical standards, and best practices across the engineering team.
• Collaborate closely with business stakeholders, architects, platform teams, and developers to deliver scalable and reliable data solutions.
• Support platform reliability, performance, security, and operational excellence through modern engineering practices.

What you'll need to succeed

• Bachelor's Degree or above in Computer Science, Statistics, Mathematics, Information Systems, or a related discipline.
• Minimum 8+ years of hands-on experience in Data Engineering, Data Platform Development, Data Architecture, or related disciplines.
• Demonstrated experience in team leadership such as leading small technical teams, mentoring junior engineers on large-scale data initiatives.
• Proven experience designing and developing data infrastructure using technologies such as PySpark, Kafka, Hadoop, or similar big data platforms.
• Strong experience building and maintaining ETL/ELT pipelines, data migration solutions, and complex integration layers between enterprise applications and centralized cloud/on-premises environments.
• Hands-on experience with modern data platforms such as Databricks (preferred), Snowflake, or similar technologies.
• Experience supporting data ingestion, transformation, and synchronization across enterprise systems such as ERP, CRM, BI platforms, and other business-critical applications.
• Experience working with at least one major cloud platform, including Microsoft Azure (preferred), AWS, or GCP.
• Experience building and supporting real-time or streaming data platforms using technologies such as Kafka, Event Hub, or equivalent solutions.
• Exposure to platform engineering and DevOps practices, including tools such as GitHub, GitLab, Azure DevOps, Docker, Kubernetes, Terraform, or similar technologies.
• Strong knowledge of data modelling, database design, and enterprise data architecture principles.
• Exposure to, or curiosity to explore, modern data, AI, and Generative AI technologies, with a willingness to continuously learn and adopt new tools and best practices.
• Proficient in spoken and written English, and currently based in Hong Kong with a valid work permit.
  
  

What you need to do now