[LPS] Data Architect

Why Work at Lenovo

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Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY). 

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Description and Requirements

Lenovo PCCW Solutions (LPS) AI Data Intelligence Practice helps enterprises become truly AI-ready through data strategy, AI readiness, data governance, modern data platforms, analytics, generative AI and managed services. The practice delivers end-to-end services across Strategy, Build and Adopt, helping clients turn enterprise data into trusted business assets and AI-ready foundations. 

We work with leading platforms and ecosystems including Microsoft Fabric, Databricks, Azure, AWS, Alibaba Cloud, Lenovo Hybrid AI, modern data governance platforms, data product frameworks, and enterprise AI technologies. 

Our clients span financial services, government and public sector, manufacturing, education, retail, hospitality, property, logistics and enterprise markets across Hong Kong and Greater China.

Role Overview 

As a Data Architect, you will design enterprise-grade AI-ready data foundations that support business intelligence, machine learning, generative AI and agentic AI solutions. You will lead architecture design, platform modernization, integration patterns and governance standards for complex enterprise data programs. 

Key Responsibilities: 

Architecture Design 

• Design target-state enterprise data architectures, reference architectures and solution blueprints. 
• Develop logical, conceptual and physical data models for enterprise analytics and AI use cases. 
• Design lakehouse, data warehouse, semantic layer and data serving architectures. 
• Define architecture patterns for data ingestion, transformation, storage, governance, security and consumption. 
• Design Customer 360, MDM, CDP and domain data product architectures. 

Platform Transformation 

• Lead data platform modernization and migration architecture across cloud, hybrid and on-premise environments. 
• Evaluate and recommend suitable technology stacks based on client requirements and constraints. 
• Establish architecture standards, design principles, governance checkpoints and reusable assets. 
• Work with engineering teams to ensure implementation aligns with architecture decisions. 

Technical Leadership 

• Conduct architecture reviews, design walkthroughs and technical decision forums. 
• Guide delivery teams on data modelling, performance, scalability, security and operability. 
• Support presales architecture, solution shaping, estimates and technical proposal development. 

Required Qualifications: 

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering or a related discipline. 
• 8+ years of experience in data architecture, solution architecture or enterprise data platform design. 
• Strong knowledge of modern data architecture patterns including lakehouse, data warehouse, semantic layer, data mesh or data products. 
• Hands-on or architecture experience with Microsoft Fabric, Databricks, Azure, AWS, Alibaba Cloud, Snowflake or equivalent platforms. 
• Strong data modelling, integration, governance and stakeholder communication skills. 

Preferred Qualifications: 

• Experience designing MDM, Customer 360, CDP, enterprise reporting or AI-ready data foundation solutions. 
• Relevant certifications such as TOGAF, Azure Architect, Databricks, AWS or equivalent. 
• Experience in regulated or complex enterprise environments. 

What Success Looks Like:

• Your architecture provides a scalable foundation for BI, ML, Gen BI and AI agent use cases. 
• Delivery teams can implement your designs consistently and efficiently. 
• Clients adopt your architecture standards as their long-term data foundation blueprint. 

Working Style:

• Collaborate with business stakeholders, architects, engineers, consultants and service delivery teams. 
• Operate in a consulting-led delivery environment with strong ownership of outcomes. 
• Contribute to reusable methodology, accelerators and solution assets for the practice. 
• Support enterprise customers in Hong Kong with occasional regional collaboration as required. 

Why Join Us:

• Join a growing AI Data Intelligence Practice focused on strategy, platform, analytics, AI and managed services. 
• Work on enterprise-scale transformation programs with modern data and AI platforms. 
• Develop cross-disciplinary capability across consulting, architecture, engineering, data products and adoption. 
• Help clients build AI-ready data foundations that support BI, ML, Gen BI and AI agents. 

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