Senior Data Product Manager - Retail Banking Services

About the role

CommBank is looking for a Senior Data Product Manager to lead the strategy, development and evolution of data products for Retail Banking Services. This is a senior leadership role at the intersection of data, technology and business strategy, working across Retail Banking Services and the broader Data community to turn complex data needs into scalable, reusable solutions that help customers and the business.

Key responsibilities

• Lead the vision, strategy and roadmap for data products, aligning investment and delivery to business priorities.
• Partner with business, technology, data engineering and Data Delivery leaders to turn business needs into scalable data products.
• Develop high-quality, reusable and well-governed data products and understand the needs of their consumers.
• Bring business context to product design, covering data structure, quality, accessibility and reuse.
• Ensure data products meet data management, metadata, risk, control and governance standards.
• Improve existing data products and strengthen relationships between data producers and consumers.
• Help standardise data-product practices and provide thought leadership on Data, AI and Analytics, mentoring data professionals.
• Partner with domain leaders to embed enterprise data-management standards.

Required profile

• Proven experience leading enterprise-level data initiatives, with a background in Data Engineering or Architecture.
• Strong stakeholder engagement and cross-functional leadership experience.
• Experience bringing together business, engineering, architecture and data-management teams.
• Experience leading, coaching or mentoring data professionals.
• Desirable: experience in Data Cloud migration and cloud data platforms, and knowledge of AI and advanced analytics.

Required skills

• Data governance, metadata management, data quality, stewardship and data management.
• Modern data engineering patterns, data modelling, architecture and integration.
• Cloud data platforms, ideally AWS and Snowflake.
• Familiarity with SQL, Python, GitHub and CI/CD environments.
• Establishing ownership, consumers, service expectations and lifecycle management for enterprise data products.