Senior Semantic Data Architect – Economics & AI Readiness

Bloomberg L P; Hong Kong; On-site; HKD 900,000 - 1,500,000; Full time

Job summary

Bloomberg L.P. in Hong Kong is seeking a Senior Data Management Professional – Semantic Modelling to shape the semantic modelling strategy for Economics data.

You will define models, ontologies, and metadata standards that make data interoperable and AI-ready, collaborating with Data, Engineering and Product teams across global contexts. The role requires strong proficiency in SQL and Python, a background in economics or data science, and proven ability to drive data governance and lineage.

Qualifications

• Bachelor's degree or equivalent in Economics, Statistics, CS, Engineering.
• Experience in semantic modelling, data management, governance, or data architecture.
• Understanding of ontologies, taxonomies, metadata, and data lifecycle.
• Proficiency in SQL, Python, or similar analytics tools.
• Strong stakeholder management and problem-solving skills.
• Fluency in English (spoken and written).

Responsibilities

• Define and drive semantic modelling strategy for Economics data.
• Develop semantic models, ontologies, taxonomies, and metadata standards.
• Collaborate with Data, Engineering and Product teams to deliver scalable data solutions.
• Ensure data interoperability, discoverability, and AI-readiness.
• Mentor colleagues and promote semantic modelling standards.
• Audit and improve data models and governance processes.

Skills

Semantic Modelling

Data Governance

Metadata Management

Ontologies & Taxonomies

SQL

Python

Stakeholder Management

English Proficiency

Education

Bachelor's degree or equivalent

Tools

SQL

Python

Job description

Bloomberg L.P. in Hong Kong is seeking a Senior Data Management Professional – Semantic Modelling to shape the semantic modelling strategy for Economics data.

You will define models, ontologies, and metadata standards that make data interoperable and AI-ready, collaborating with Data, Engineering and Product teams across global contexts. The role requires strong proficiency in SQL and Python, a background in economics or data science, and proven ability to drive data governance and lineage.