Senior Data Analyst #ESY
Summary
Design enterprise data models and semantic layers in Snowflake to support self-service analytics, reporting, and GenAI use cases for HR and business stakeholders.
Enterprise Data Modelling
· Define, maintain and enhance enterprise data models across key business domains including Customer, Policy, Product, Distribution, Claims, Finance and Operations.
· Develop conceptual, logical and physical data models aligned to target data architecture and analytics priorities.
· Identify and close data model coverage gaps across core source systems and analytical platforms.
· Establish common business definitions, entities, attributes and relationships across business domains.
· Partner with business stakeholders, Data Engineers and Solution Architects to translate business requirements into scalable data models.
Semantic Layer & AI/GenAI Enablement
· Design and maintain semantic models to support self-service analytics, reporting and AI-enabled use cases.
· Build and maintain Snowflake semantic layers and business-friendly data structures for analytics consumers.
· Support adoption of GenAI and AI agent use cases through well-defined business terminology, metrics and semantic relationships.
· Define reusable business metrics, hierarchies, dimensions and measures for enterprise-wide consistency.
Data Product Design & Documentation
· Work closely with Data Engineering teams to translate data models into implementation specifications.
· Produce mapping documents, business glossaries, metadata definitions, lineage documentation and model diagrams.
· Support onboarding of new data sources and integration into the enterprise data model.
· Review proposed data structures and ensure alignment with enterprise modelling standards.
Stakeholder Engagement
· Collaborate with Finance, Distribution, Operations, Product and Technology teams to understand business concepts and modelling requirements.
· Facilitate workshops to define enterprise business entities, relationships and standard definitions.
· Support strategic initiatives such as enterprise reporting, self-service analytics, Snowflake adoption and AI/GenAI programmes.
Requirements
Experience
· 2-3+ years of experience in Data Modelling, Analytics Engineering, Semantic Layer Development or related disciplines.
· Hands-on experience supporting semantic layer design or development, including defining business-friendly entities, dimensions, measures, metrics, hierarchies, joins and relationships for analytics consumption.
· Experience translating business terminology and reporting requirements into reusable semantic models, business definitions and implementation-ready specifications.
· Strong knowledge of conceptual, logical and physical data modelling techniques.
· Strong SQL skills and experience working with large-scale data platforms.
· Experience producing ERDs, business glossaries, metadata documentation and source-to-target mapping specifications.
· Ability to bridge business stakeholders and technical teams, translating business requirements into data models and engineering-ready specifications.
Technical Skills
· Snowflake experience is strongly preferred, including experience working with curated data models, analytical views and business-facing data structures.
· Good understanding of semantic layer development, including defining business entities, dimensions, measures, metrics, joins, hierarchies and reusable business definitions.
· Experience designing semantic models that support self-service analytics, dashboarding, reporting and AI/GenAI-enabled data consumption.
· Ability to translate business terminology into structured semantic models that can be consumed by analytics tools, BI platforms and AI agents.
· Experience with metrics modelling, business glossary design, data product modelling, metadata management and source-to-target mapping will be advantageous.
· Knowledge or experience with Oracle Cloud, AWS S3 and Airflow will be advantageous.
· Understanding of GenAI, AI agents, knowledge graphs, business ontologies or semantic models will be advantageous.
Education
· Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Management Information Systems or a related field.
Interested candidates, please email your resume to annasee@recruitexpress.com.sg
Anna See Sing Yee
CEI Reg R25157535
Recruit Express Pte Ltd
EA License No: 99C4599
We regret that only shortlisted candidates will be contacted