Are you a strategic data professional ready to drive enterprise-level transformation? We are seeking a highly skilled Lead Data Engineer to partner with cross-functional teams in Hong Kong. In this role, you will evaluate emerging technologies, engineer scalable cloud services, and build robust ETL pipelines. Serving as a crucial bridge between data engineering, operations, and business strategy, the successful candidate will empower stakeholders to harness data for actionable insights and commercial success.
about the company.
Our client is a premier public institute. Renowned for its commitment to sustainability and technological innovation, they invest heavily in modern cloud platforms, data analytics, and AI technologies to drive operational excellence, support the region's energy transition, and deliver unparalleled reliability to their vast customer base.
about the team.
You will be joining a high-performing, cross-functional technology hub comprising Data Architects, Data Scientists, and Data Engineers. Reporting directly to the Head of Technical Delivery, this highly collaborative team champions knowledge sharing, secure-by-design principles, and continuous technical upskilling within a large-scale enterprise environment.
... about the job.
- Act as the hands-on technical anchor for Data Engineering and DevOps initiatives.
- Architect, scale, and maintain high-performing ETL pipelines for both structured and unstructured data, ensuring strict data reliability.
- Design and optimise CI/CD workflows covering ETL processes, data assets, cloud infrastructure, and web applications.
- Evaluate and enhance the data platform to maximise cost-efficiency and improve the developer experience (e.g., monitoring cloud expenditure).
- Serve as a core platform administrator, collaborating with business analysts, project managers, and data scientists to deliver tailored data solutions.
- Champion best practices in cloud engineering, data security, and DevOps methodologies across the team.
- Leverage modern AI-assisted tools to accelerate development cycles and boost overall delivery productivity.
- Partner with external vendors and IT service providers for solution architecture, technical support, and BAU system delivery.
- Define, track, and visualise key performance indicators (KPIs) to ensure optimal platform health.
- Elevate enterprise data governance standards and data quality frameworks across the analytics ecosystem.
skills & experiences required.
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a closely related technical discipline.
- Minimum 10 years of hands-on experience spanning Data Engineering, Data Analytics, Platform Engineering, or DevOps. (Candidates demonstrating exceptional potential but with fewer years of experience may be considered for a Mid-Level Data Engineer capacity).
- Proven expertise in modern cloud data architectures, with a strong preference for Azure Databricks (PySpark) and governance frameworks (e.g., Unity Catalog).
- Deep hands-on experience with cloud ecosystems, specifically Microsoft Azure.
- High proficiency in Git, Jira, Azure DevOps, Python, SQL, shell scripting, and Terraform.
- Familiarity with containerisation and orchestration technologies (e.g., Kubernetes, Helm, Istio) is a distinct advantage.
- Prior exposure to Oracle ERP deployments or modern web application frameworks (e.g., Spring Boot, FastAPI, Vue.js) is highly desirable.
- Proven experience utilising AI coding assistants (e.g., GitHub Copilot, OpenAI Codex, Claude Code) to enhance individual and team-level efficiency.
- Exceptional sense of ownership, proactive problem-solving abilities, and robust time-management skills.
- Outstanding communication and translation skills, with the ability to demystify complex technical concepts for diverse commercial stakeholders.
If you are interested in this role, please click 'Apply Now' or send your CV directly to [heather.yin@randstad.com.hk].
