At AustralianSuper, we truly care about our colleagues. We know work and life are intertwined. That’s why we support the diverse needs of everyone and have policies that enable us all to thrive and be truly flexible. We ensure diversity is celebrated for the opportunity it provides us all to learn and grow and deliver better outcomes for members. We are dedicated to building a high-performance environment underpinned by a strong risk culture, ensuring we deliver the best outcomes for our members.

Your New Role 

Reporting to the Head of Finance, Performance & Business Partnering, the Principal, Finance Data & Analytics is responsible for defining and delivering the enterprise Finance data and analytics strategy. The role exists to lift the speed, quality, consistency, and usefulness of financial data and insights across the organisation, enabling stronger decision‑making and more effective performance management.

The role brings coherence to Finance data, analytics, and reporting by establishing clear standards, scalable solutions, and fit‑for‑purpose insights, reducing fragmentation, duplication, and manual effort across Finance teams.

Key Responsibilities:

• Develop and own the enterprise‑wide Finance data, analytics, and AI strategy, aligned to performance, regulatory, and decision‑making needs.
• Define the future‑state Finance data and analytics architecture, including reporting, dashboards, metrics, and advanced analytics use cases.
• Act as the Finance Data, Analytics, and AI Centre of Excellence, setting direction for tools, analytical approaches, and capability across the Finance domain.
• Provide expert guidance and thought leadership on complex or material initiatives, with direct involvement in higher‑impact projects where needed, while progressively lifting capability across
• Operates as an enabling role, setting direction, standards, and capability, rather than owning all analysis centrally
• Establish clear principles for how Finance data is structured, governed, and consumed across the organisation.
• Partner closely with the Technology, Digital and Data Domain, and broader enterprise teams to ensure Finance data capabilities support current and future decision‑making needs
• Works closely with Heads of Finance across business units to understand performance and analytics needs.

People and Fund Leadership

• Act as the enterprise subject‑matter expert for Finance data and analytics.
• Provide clear guidance, tools, and capability uplift to Finance teams, without centralising day‑to‑day business‑unit analytics delivery.

What You’ll Need   

• Significant experience in finance data, analytics, performance reporting, financial systems, or data governance within a complex, regulated organisation.
• Strong understanding of end‑to‑end Finance processes (e.g. performance management, reporting, forecasting, financial control) and how data underpins decision‑making and assurance.
• Demonstrated experience designing and implementing enterprise‑level data, analytics, or reporting strategies that deliver practical business outcomes.
• Experience operating within robust governance and control environments, with a sound understanding of regulatory, audit, and risk expectations relating to finance data.
• Exposure to large‑scale finance transformation initiatives and the data implications of major system or operating model change.
• Familiarity with modern analytics, data platforms, and emerging AI use cases as applied pragmatically within Finance (depth over hype).

• Develop and own the enterprise‑wide Finance data, analytics, and AI strategy, aligned to performance, regulatory, and decision‑making needs.
• Define the future‑state Finance data and analytics architecture, including reporting, dashboards, metrics, and advanced analytics use cases.
• Act as the Finance Data, Analytics, and AI Centre of Excellence, setting direction for tools, analytical approaches, and capability across the Finance domain.
• Provide expert guidance and thought leadership on complex or material initiatives, with direct involvement in higher‑impact projects where needed, while progressively lifting capability across
• Operates as an enabling role, setting direction, standards, and capability, rather than owning all analysis centrally
• Establish clear principles for how Finance data is structured, governed, and consumed across the organisation.
• Partner closely with the Technology, Digital and Data Domain, and broader enterprise teams to ensure Finance data capabilities support current and future decision‑making needs
• Works closely with Heads of Finance across business units to understand performance and analytics needs.
• Act as the enterprise subject‑matter expert for Finance data and analytics.
• Provide clear guidance, tools, and capability uplift to Finance teams, without centralising day‑to‑day business‑unit analytics delivery.

• Finance data
• Analytics
• Performance reporting
• Financial systems
• Data governance
• End-to-end Finance processes (e.g. performance management, reporting, forecasting, financial control)
• Enterprise-level data, analytics, or reporting strategies
• Robust governance and control environments
• Regulatory, audit, and risk expectations relating to finance data
• Large-scale finance transformation initiatives
• Modern analytics
• Data platforms
• Emerging AI use cases

• Significant experience in finance data, analytics, performance reporting, financial systems, or data governance within a complex, regulated organisation.
• Strong understanding of end‑to‑end Finance processes (e.g. performance management, reporting, forecasting, financial control) and how data underpins decision‑making and assurance.
• Demonstrated experience designing and implementing enterprise‑level data, analytics, or reporting strategies that deliver practical business outcomes.
• Experience operating within robust governance and control environments, with a sound understanding of regulatory, audit, and risk expectations relating to finance data.
• Exposure to large‑scale finance transformation initiatives and the data implications of major system or operating model change.
• Familiarity with modern analytics, data platforms, and emerging AI use cases as applied pragmatically within Finance (depth over hype).