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Data Architect and Team Lead

Exclusive opportunity

Onsite

Data Architect and Team Lead

Automated Systems (H.K.) Limited

Data Architect and Team Lead

Skills

Data EngineeringTesting & QADatabricksMachine LearningAIPerformance ManagementPower BIAzure

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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