Senior Technical Product Manager - Data Platforms and Infrastructure

About the position

At Vanguard, we don't just have a mission—we're on a mission. To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work
Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

Responsibilities
• Full product lifecycle ownership : Own the product vision and strategy of Vanguard’s data platforms from incubation to sunset , in alignment with Vanguard’s enterprise data strategy and target state architecture.
• Customer-centric p roduct ideation : Monitor market trends and conduct user research to i dentify opportunities that will define data platform products and product features C ollaborat e across divisions with our users (e.g., data engineers, architects, analysts, data scientists) to define data products tha t meet their critical data and business needs
• Foster a culture of experimentation through MVPs, rapid prototyping, and iterative development , encouraging bold thinking while maintaining a strong bias for execution and learning.
• Translate insights into actionable and prioritized product features Product delivery through innovation , experimentation , and continuous improvement
• Develop and maintain a transparent, outcomes-based roadmap and backlog, partnering and aligning with key stakeholders, including architecture and engineering functions under the CTO, to sequence capabilities based on business priorities and technical feasibility
• Collaborate with data architecture and engineering teams to co-create the right features, often leading technical discussions with a deep understanding of data platforms and technologies (e.g., AWS, Databricks, Snowflake, integration patterns)
• Conduct usability testing and experimentation to ensure platform features meet user needs
• Manage product launches , coordinating with project managers for on-time and on-budget releases
• Define and monitor key product metrics and analyze product performance to continually improve and drive value, inform roadmap and investment decisions , and measure success
• Funding and P&L Partner with finance and engineering leadership to allocate budgets across the product portfolio
• Use data-driven frameworks to d efine and manage the OKRs , P &L, and value realization (ROI) of core platform capabilities and data services
• Go-to-market and adoption: Develop and execute go-to-market (GTM) strategies in partnership with enablement , communications , and other support teams
• Create approach to socialize products and products features along with onboarding and training materials to ensure adoption
• Building out the product function S hape a high-performing product culture within the data platform organization , while fostering a culture of innovation and bold thinking
• Mentor junior PMs and contribute to the growth of the product management capability within EDA&E

Requirements
• Undergraduate degree or equivalent combination of training and experience required.
• Minimum of eight years related business experience.
• Three years of leading large cross-functional teams on major organizational projects preferred.

Nice-to-haves
• Graduate degree preferred.
• Demonstrated end-to-end product ownership across product lifecycle , including product innovation and delivery through ideation and experimentation, GTM , and product evolution in a fast-paced and dynamic environment
• Ability to lead strategic discussions on data architecture and engineering (e.g., data modeling, metadata management, data quality, data integration, storage, compute, security) and data platforms (e.g., AWS, Databricks, Confluent, Flink)