Role Overview

We are seeking an authoritative Lead Data Platform Architect with 15+ years of experience to spearhead the design, engineering, and productization of our enterprise cloud data platforms. Operating at the intersection of business strategy and hands-on architecture, you will turn complex business requirements into scalable, secure, and governed analytical products using Microsoft Fabric, Azure Databricks, and AWS.

You bring a true product-engineering mindset-moving beyond raw infrastructure to "solutionize" data platforms into measurable business products (such as enterprise catalogs and self-service data domains). You are equally comfortable defining a 3-year AI-driven automation vision, designing rapid architectural prototypes, and mentoring high-performing engineering teams.

Key Responsibilities

1. Enterprise Data Architecture & Product Engineering

• Business-Aligned Architecture: Partner directly with business leads to translate strategic requirements and KPIs into scalable data platform architectures.
• Platform Productization: Treat the data platform as a product-designing and delivering reusable data products and enterprise data catalogs (e.g., Unity Catalog on Databricks) aligned with strict governance principles on rapid delivery cycles.
• End-to-End Platform Delivery: Architect, build, deploy, and operate secure cloud-native data ecosystems spanning foundational infrastructure, large-scale batch/streaming ingestion, and production support.

2. Cloud Infrastructure, DevOps & AI-Driven CI/CD

• Infrastructure-as-Code (IaC): Standardize and automate cloud provisioning across Azure and AWS using Terraform and Bicep.
• Next-Generation CI/CD: Eliminate deployment bottlenecks by embedding AI-assisted tooling (e.g., Codex/Copilot) into CI/CD pipelines-automating code reviews, handling business process exceptions, improving prediction accuracy, and reducing manual human intervention over a 3-year modernization roadmap.

3. Technical Leadership & Team Enablement

• Mentorship & Culture: Lead, mentor, and run regular checkpoints with data engineering teams to foster psychological safety, clear alignment, and sustainable delivery velocity.
• Complex Problem Solving: Step in as the technical escalation point to resolve architectural bottlenecks, data integration silos, and multi-platform processing challenges.

Qualifications & Requirements

• Experience: 15+ years of experience in data engineering, cloud infrastructure, and enterprise data architecture across large enterprise or public-sector environments.
• Core Data Platforms (Mandatory): Deep, hands-on architectural mastery of Microsoft Fabric and Azure Databricks (including Unity Catalog, Delta Lake, and enterprise governance).
• Multi-Cloud & IaC: Extensive expertise in the Microsoft Azure data and infrastructure stack, strong working knowledge of AWS, and mastery of Terraform or Bicep.
• Architectural & Product Mindset: Proven ability to turn raw platform capabilities into business-facing data products, solve cross-platform data silos, and deliver rapid architectural proofs-of-concept.
• DevOps & Automation Vision: Deep familiarity with CI/CD pipeline architecture, identifying deployment pain points, and leveraging AI/LLM code-analysis tools to automate operational governance.
• Leadership & Communication: Proven track record leading engineering teams, communicating architectural trade-offs to executive stakeholders, and cultivating high-morale technical teams.
• Location: Based in Hong Kong or willing to relocate to Hong Kong.

Technical Stack

• Data Platforms: Microsoft Fabric, Azure Databricks, Unity Catalog, Delta Lake
• Cloud & Infrastructure: Microsoft Azure, AWS, Terraform, Bicep
• Data Engineering & DevOps: Batch & Streaming Architectures, CI/CD Automation, AI-Assisted DevOps (Codex/GitHub Copilot), Data Governance & Security