Enterprise Data Platform & AI Product Lead

Republic Polytechnic

Singapore

On-site

SGD 110,000 - 170,000

Full time

6 days ago
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Job summary

Republic Polytechnic in Singapore is seeking a Deputy Manager, Data Hub & Data Products to design, develop and operationalise an enterprise Data Hub.

You will work with Schools and business stakeholders to translate requirements into scalable data models and data products, overseeing data architecture, integration, delivery, and vendor engagements to ensure AI-ready, reusable data assets for analytics and decision-making.

Qualifications

  • At least five years in Data Warehousing, Enterprise Data Management, Data Architecture, Data Modelling or Data Engineering.
  • Experience delivering enterprise-scale data platforms and managing vendors/technology implementations.
  • Experience in education/public sector or large complex organisations is advantageous.

Responsibilities

  • Lead Data Product Management for enterprise data products.
  • Translate business requirements into data product requirements, user stories and roadmaps.
  • Drive adoption and usage of Data Hub data products across RP.
  • Design and maintain enterprise data models for analytics and AI use cases.
  • Support data architecture, integration and vendor collaboration.
  • Review ETL/ELT pipelines and data quality processes; onboard new sources.
  • Manage vendor engagements and ensure knowledge transfer.

Skills

Data Warehousing
Dimensional Modelling
Star Schemas
Snowflake Schemas
Modern Data Architecture
ETL/ELT Design
Master Data Management
Metadata Management
Data Quality Management
Microsoft Fabric
Azure Data Services
Stakeholder Communication
Facilitation
Bridge Teams

Education

Information Systems or Computer Science or Data Analytics or Data Engineering

Job description

Republic Polytechnic in Singapore is seeking a Deputy Manager, Data Hub & Data Products to design, develop and operationalise an enterprise Data Hub.

You will work with Schools and business stakeholders to translate requirements into scalable data models and data products, overseeing data architecture, integration, delivery, and vendor engagements to ensure AI-ready, reusable data assets for analytics and decision-making.

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