General Manager Data & AI Engineering Delivery

About the role

The General Manager Data & AI Engineering Delivery leads the engineering and delivery capability behind the organisation's data and AI ambitions. Reporting to the Chief Data & AI Officer, the role turns data and AI priorities into production-ready data products and engineering practices, ensuring reuse of secure, scalable data pipelines and transformations. It is a permanent, full-time position based in Bengaluru.

Key responsibilities

• Lead the Data and AI engineering function, including capability development, standards and ways of working
• Establish and embed modern engineering practices (Agile, DevOps, DataOps) across teams
• Design, build and reuse secure, scalable data pipelines and transformations
• Deliver reusable, high-quality data products supporting business applications, advanced analytics and AI/ML outcomes
• Provide production-ready data outputs for AI and ML model development
• Define and enforce engineering standards, frameworks and best practices
• Ensure high standards of data quality, lineage and observability
• Oversee end-to-end delivery of data and AI engineering initiatives and manage prioritisation and backlogs across teams
• Partner with architecture, governance, AI portfolio and platform teams, and align delivery to enterprise architecture, data governance and AI strategy
• Ensure compliance with security, privacy and regulatory requirements, and drive improvements in efficiency and automation

Required profile

• Proven leadership of large engineering and delivery teams at scale
• Master's degree or PhD in Computer Science, Engineering, Actuarial Studies, Data Science or AI, with hands-on enterprise deployment experience in financial services
• Deep understanding of modern data lakehouse architecture, data fabric and AI model architecture
• Deep understanding of financial data, fraud detection and credit scoring

Required skills

• Data engineering, data pipelines and large-scale data processing
• AI/ML data enablement and integration with engineering workflows
• Modern data architectures (data lakes, warehouses, streaming, data mesh)
• Cloud-based data platforms and engineering tools
• DataOps, DevOps and agile delivery practices
• Data governance, quality, lineage and security

ANZ offers flexible working options, including hybrid work where the role allows it, and a range of benefits including health and wellbeing services. Applications are made through the ANZ careers site using reference number 127086.