Senior Data Analyst ESY

recruit express pte ltd; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Recruit Express Pte Ltd in Singapore seeks an Enterprise Data Modeller to define and maintain enterprise data models across customer, policy, product, distribution, claims, finance and operations. You will align conceptual, logical and physical models with the data architecture and analytics priorities.

Collaborating with Data Engineers and Solution Architects, you will translate business requirements into scalable data models, establish definitions and metadata, and support analytics through a

Qualifications

• Experience in data modelling across enterprise domains (customer, policy, product, distribution, claims, finance, operations).
• Hands-on experience with semantic layer design and development for analytics consumption.
• Ability to translate business terminology into reusable semantic models and implementation-ready specs.

Responsibilities

• Define, maintain and enhance enterprise data models across key business domains.
• Develop conceptual, logical and physical data models aligned to target data architecture.
• Identify and close data model coverage gaps across core source systems and analytical platforms.
• Establish common business definitions, entities, attributes and relationships.
• Partner with stakeholders, Data Engineers and Solution Architects to translate requirements into scalable data models.

Skills

Data modelling

Analytics engineering

Semantic layer development

SQL skills

Stakeholder bridging

Education

Bachelor’s degree in Computer Science

Tools

Snowflake

Oracle Cloud

AWS S3

Airflow

Job description

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.