Responsibilities:
- Define and manage data architecture strategy, including scalable data models and target-state designs aligned with business goals
- Establish standards for ETL, data governance, and data quality across the data platform
- Design and oversee modern data platforms, including pipelines, CI/CD processes, and containerized deployments
- Act as a bridge between data and infrastructure teams by translating data requirements into technical specifications and reviewing IaC deliverables
- Define observability, reliability, and recovery standards for data systems.
- Conduct technical reviews, support incident resolution, and drive continuous platform improvements.
- Promote DataOps practices, evaluate new technologies, and mentor data engineering teams.
Requirements:
- Degree in Computer Science, IT, or related disciplines.
- 7+ years of experience across data engineering and cloud/data architecture, with prior technical leadership exposure.
- Strong expertise in Azure data services (e.g., Databricks, Data Factory, Synapse, Data Lake).
- Solid knowledge of data architecture concepts (e.g., data modeling, Lakehouse, Medallion architecture).
- Familiarity with Infrastructure-as-Code (e.g., Terraform, Ansible) and ability to review code.
- Understanding of CI/CD, containerization (Docker/Kubernetes), and version control practices.
- Strong communication skills with the ability to bridge technical and business teams.
- Strategic mindset, leadership capability, and experience working in collaborative, multicultural environments.
Click "Apply Now" to apply for this position or call Stella Tang at +852 3180 4977 for a confidential discussion. All information collected will be kept in strict confidence and will be used for recruitment purpose only.
