Automated Systems (H.K.) Limited
Data Architect and Team Lead
Skills
14 days ago
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Important information
Contract type:
Permanent
Work mode:
Onsite
Published on:
12 October 2026
What they need
Key Responsibilities
Team Leadership & Account Management
- Act as the primary point of contact for clients, overseeing account servicing, issue resolution, and resource planning.
- Lead and manage a team of data engineers, including performance management, mentoring, and workload allocation.
- Represent the team in client engagements, including sprint planning and task prioritization sessions.
- Ensure effective communication between technical teams and business stakeholders.
Data Architecture & Platform Design
- Design, develop, and evolve scalable data architectures, including data pipelines, data models, and platform components.
- Document current-state systems, including workflows, dependencies, and configurations, and define future-state architecture strategies.
- Lead proof-of-concept (PoC) initiatives to validate new technologies and architectural approaches.
- Ensure solutions meet performance, scalability, and maintainability requirements.
Data Engineering & Delivery
- Oversee end-to-end data platform development, from design to deployment.
- Provide hands-on guidance in data engineering, data modelling, and platform implementation (Azure, Databricks).
- Drive best practices in DevOps, automation, and ML integration within data workflows.
Quality Assurance & Governance
- Review and validate technical deliverables, including architecture designs, code, and documentation.
- Establish and enforce standards for data governance, testing (SIT), and documentation.
- Ensure consistency, reliability, and quality across all technical outputs.
Technical Support & Continuous Improvement
- Lead troubleshooting efforts and coordinate with vendors or platform providers to resolve technical issues.
- Promote continuous improvement through adoption of emerging technologies such as AI/ML, Agentic AI, and modern data tooling.
Qualifications
- Minimum 8 years of experience in data management and governance.
- Minimum 5 years of hands-on experience in data engineering.
- At least 3 years of experience with Azure and Databricks (development, testing, deployment).
- Minimum 3 years of team leadership and performance management experience.
- At least 2 years of experience in data pipeline design and data modelling.
Skills & Requirements
- Strong hands-on experience in data engineering, data modelling, DevOps, ML automation, and building data platforms end-to-end.
- Familiarity with Azure Data Factory and Power BI is an advantage.
- Proven ability to define and maintain technical documentation standards.
- Strong leadership, communication, and stakeholder management skills.
- Demonstrated interest in emerging technologies (e.g., Azure ecosystem, Databricks, AI/ML, Agentic AI).
- Proven track record of successful project delivery.
- Proficiency in English is required; Cantonese and/or Mandarin is an advantage.
- Strong ability to read, write, and review technical documentation in English.
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