Enterprise Data Architecture Lead for Scalable Analytics

Pinpoint Asia; Hong Kong; On-site; HKD 600,000 - 1,000,000; Full time

Job summary

Pinpoint Asia partners with a leading financial services firm in Hong Kong to modernize its data landscape for analytics, AI use cases, and daily operations. You will translate business requirements into scalable data models that support enterprise decisions.

You’ll own the full data modeling lifecycle from discovery to source-to-target mapping, build conceptual/logical/physical models, and collaborate with data engineers to deploy models across lakehouse tables, databases, APIs, and semantic

Qualifications

• 5+ years of dedicated experience in data modeling, architecture, or business intelligence.
• Hands-on experience with modeling tools like Erwin Data Modeler or ER/Studio.
• Excellent SQL skills for data profiling and validation.
• Deep understanding of relational modeling, normalization, dimensional modeling, and slowly changing dimensions.
• Ability to negotiate with and present complex models to non-technical business SMEs.
• Bonus: Insurance domain experience and exposure to cloud/lakehouse environments.

Responsibilities

• Translate business requirements into scalable data models for the enterprise.
• Run the full data modeling lifecycle from discovery to source-to-target mapping and model validation.
• Build and maintain conceptual, logical, and physical models.
• Design schemas tailored to use cases, including dimensional, normalized, and canonical models.
• Partner with data engineers to push models into production across databases, lakehouse tables, APIs, and semantic layers.
• Establish data quality rules, lineage, and governance controls for sensitive information.

Skills

SQL

Data modeling

Erwin

ER/Studio

Dimensional modeling

Communication

Tools

Erwin Data Modeler

ER/Studio

Job description

Pinpoint Asia partners with a leading financial services firm in Hong Kong to modernize its data landscape for analytics, AI use cases, and daily operations. You will translate business requirements into scalable data models that support enterprise decisions.

You’ll own the full data modeling lifecycle from discovery to source-to-target mapping, build conceptual/logical/physical models, and collaborate with data engineers to deploy models across lakehouse tables, databases, APIs, and semantic