Client: The client is a premier institution offering world-class postgraduate business education, including MBA, Executive MBA, and specialised finance and management programs. Its mission is to transform global business practices. The client is globally recognized for its rigorous academics, exceptional faculty, and cutting-edge research. It consistently ranks among the world’s top business schools, securing high positions in global MBA rankings. The client fosters leadership and innovation, equipping students for impactful careers in the international business landscape.
Project overview: The Client recently completed their Data & AI Strategy and Roadmap, establishing a foundation for a data-driven future. The assessment phase reviewed the current state of Data and AI, analyzing technology, processes, resources, and structure, and provided strategic recommendations aligned with the School’s 5-year transformation plan. Building on this, the discovery phase focused on data governance, use cases, business drivers, service offerings, technology, and roles, delivering further strategic insights. With this groundwork complete, The Client is now entering the delivery phase, which includes implementing a Data Platform, a first use case, and establishing Data Governance roles, processes, and technologies.
Technology stack: Databricks, MS stack, Azure Data Factory, MS Fabric
- Responsibilities: Lead the technology and architecture for the Data Team, ensuring alignment with project objectives
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Manage the performance of the data platform, including the design and execution of data quality measurement processes
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Define and implement development standards and processes to ensure consistency and scalability
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Make critical decisions on data modeling and platform design to optimize data architecture
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Collaborate with the AI Innovation Lab to integrate emerging technologies and drive innovation within the data platform
- 5+ years of experience in data platform architecture and design
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Proven experience leading and mentoring technical teams
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Advanced knowledge of data modeling and performance optimization
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Practical experience with Databricks, Azure Data Factory, and Microsoft Fabric