Chief Enterprise Data and Analytics Officer

Enterprise data and analytics strategy

• Lead the development and execution of the enterprise data and analytics strategy aligned to business and DD&AI priorities.
• Define a clear roadmap covering data governance, data management, analytics capability and data accessibility.
• Ensure the strategy balances foundational uplift with delivery of business value.
• Provide enterprise direction on how data and analytics will support improved decision-making and performance.

Data Quality, Capability and Availability

• Support the evolution of enterprise data platforms and architecture (e.g. cloud data platforms such as Snowflake) to enable scalable, secure, and high-performing data environments
• Drive the development of modern data engineering, data management, and analytics capabilities
• Ensure data assets are accessible, well-managed, and aligned to business needs
• Ensure critical data is accessible, well-structured and fit for operational, analytical and regulatory use.
• Support the development of enterprise data models and standards to enable reuse and consistency.
• Partner with technology to ensure data platforms support scalable and secure access to data.
• Improve the quality, consistency and reliability of enterprise data assets.

Analytics, Insights & AI Enablement

• Build and lead enterprise analytics and insight capabilities, enabling data-driven decision making across the organisation
• Partner with business units to identify and prioritise high-value analytics and AI use cases and prioritise opportunities where high-quality data can unlock value while working closely with AI, Digital and Technology teams
• Enable the effective use of advanced analytics, AI and machine learning models, ensuring strong governance across their lifecycle
• Deliver insights that improve customer experience, growth, and operational efficiency
• Ensure data is structured, governed and accessible in a way that enables industry leading AI and advanced analytics solutions
• Provide guidance on data readiness, feasibility and dependencies for AI initiatives.
• Ensure appropriate governance is in place around data inputs into AI models, including quality, bias and traceability.

Business Partnership & Value Delivery

• Partner with senior stakeholders across CBW, IBB, PSM, Technology and other functions to align data and analytics priorities to business outcomes
• Align enterprise data efforts to key business outcomes such as growth, efficiency, customer experience and risk management.
• Translate business needs into data and analytics solutions and roadmaps
• Ensure delivery is prioritised and sequenced based on enterprise value.
• Drive measurable outcomes including customer experience uplift, revenue growth, productivity gains, and risk reduction
• Provide clear and pragmatic advice to executives on data-related decisions, trade-offs and risks.

Leadership & Capability Development

• Build, lead and develop a high-performing enterprise data and analytics function
• Attract and retain critical capabilities to support Westpac NZ’s data ambition
• Drive a data-led culture across the organisation, lifting data literacy and adoption
• Define and evolve the operating model to balance enterprise standards with business alignment.
• Work closely with Digital, Technology and AI teams to ensure clarity of roles, responsibilities and interfaces.
• Lead through influence across a complex, matrixed environment.

Risk, Compliance & Governance, Ownership and control

• Establish and maintain strong enterprise data governance frameworks including ownership, stewardship, quality and lifecycle management.
• Strengthen the data control environment across the full data lifecycle, ensuring alignment to regulatory and risk requirements.
• Embed clear accountability for data across business and functional units.
• Improve transparency of data lineage, definitions and usage across the organisation.

• Embed strong risk management and control frameworks across data and analytics activities
• Ensure effective governance of AI/ML models, including model risk management and regulatory compliance
• Work closely with Risk, Legal and Compliance to ensure alignment with Westpac’s risk appetite and regulatory obligations

Stakeholder & External Engagement

• Provide trusted advice to executives and senior leaders on data and analytics opportunities, risks and trade-offs
• Manage key vendor and partner relationships to optimise performance, innovation and cost
• Engage with regulator