[What the role is]

[What you will be working on]

1. Data Product Management
•    Support the development and delivery of enterprise data products aligned with IHL's strategic priorities.
•    Work with business stakeholders to understand business needs, data requirements and desired outcomes.
•    Translate business use cases into data product requirements, user stories and delivery roadmaps.
•    Prioritise data product improvements based on business value and institutional impact.
•    Drive adoption and usage of Data Hub data products across the institute.
•    Monitor data product performance, usage and business outcomes.
•    Support the implementation of Data-as-a-Service (DaaS) capabilities.

2. Enterprise Data Modelling
•    Design and maintain conceptual, logical and physical data models for enterprise-wide data domains.
•    Develop scalable data models that support analytics, operational reporting and AI use cases.
•    Define and maintain business entities, relationships, business rules and metadata.
•    Ensure consistency and alignment of data definitions across systems and domains.
•    Support the development of enterprise semantic models and reusable datasets.
•    Collaborate with Data Owners and Data Stewards to establish trusted data definitions.

3. Data Architecture and Integration
•    Support the Lead Data Architect in designing enterprise data architecture and target-state Data Hub architecture.
•    Review solution designs proposed by vendors and ensure alignment with enterprise architecture principles and standards.
•    Support data ingestion, transformation, integration and data lifecycle design activities.
•    Assess scalability, performance, maintainability and usability of architecture solutions.
•    Contribute to enterprise data architecture blueprints, standards and reference architectures.
•    Ensure effective integration across enterprise applications, learning systems and analytics platforms.

4. Data Warehouse and Data Hub Delivery
•    Lead technical discussions relating to design and implementation.
•    Review ETL/ELT pipelines, data transformation logic and data quality processes.
•    Support onboarding of new source systems into the Data Hub.
•    Identify data quality, performance and integration issues and coordinate resolution efforts.
•    Support testing, validation and release activities for Data Hub initiatives.
•    Ensure data assets are AI-ready, reusable and scalable.

5. Vendor and Technical Management
•    Provide day-to-day oversight of external vendors delivering Data Hub solutions.
•    Review vendor deliverables, technical documentation and implementation approaches.
•    Challenge proposed designs where necessary and ensure solutions meet business requirements.
•    Perform root cause analysis of data-related issues and coordinate resolution.
•    Be hands-on in investigating data pipeline failures, integration issues, data discrepancies and performance bottlenecks.
•    Escalate delivery, architecture or quality issues when required.
•    Ensure knowledge transfer and documentation are completed by vendors.

[What we are looking for]

•    Qualification in Information Systems, Computer Science, Data Analytics, Data Engineering or related discipline.

Experience
•    At least 5 years of experience in:
o    Data Warehousing
o    Enterprise Data Management
o    Data Architecture
o    Data Modelling
o    Data Engineering
o    Business Intelligence or Analytics Platforms
•    Experience delivering enterprise-scale data platforms.
•    Experience managing vendors and technology implementation projects.
•    Experience working in education, public sector or large complex organisations is advantageous.
•    Familiarity with IHL business processes and data domains is highly desirable.

Knowledge & Skills
•    Strong knowledge of: 
o    Data Warehousing concepts
o    Dimensional Modelling
o    Star and Snowflake Schemas
o    Modern data architecture principles
o    ETL / ELT design
o    Master and Reference Data Management
o    Metadata Management
o    Data Quality Management
o    Microsoft Fabric, Azure Data Services
•    Ability to communicate effectively with both technical and non-technical stakeholders.
•    Strong facilitation, negotiation and influencing skills.
•    Ability to bridge business, technology and data teams.