About this role
About Us
At ANZ, we're shaping a world where people and communities thrive, driven by a common goal: to improve the financial wellbeing and sustainability of our millions of customers.
Within our technology team we are applying new ways technology and data can be harnessed as we work towards a common goal: to improve the financial wellbeing and sustainability of our millions of customers.
Our community of over 5,000 engineers is key to making this happen, because technology underpins every part of our business - from delivering tools, apps and services for our customers, to building a bank for the future.
About the Role
The GM – Data and AI Engineering, Delivery is responsible for leading the engineering and delivery capability that underpins the organisation’s data and AI ambitions. This role ensures the reuse of enterprise-wide secure, scalable, and high-quality data pipelines, transformations, and build out of the data products to support business use-cases/ outputs, business applications, advanced analytics and AI/ ML outcomes.
Reporting to the Chief Data & AI Officer, this role bridges strategy and execution, translating data and AI priorities into reliable, production-ready data products and engineering practices. You will drive reuse, automation and embrace cross-divisional ways of working, and standardised delivery models that support efficient, high-quality outcomes across the enterprise.
As a senior leader, you will partner closely with architecture, governance, AI portfolio teams, and business stakeholders to ensure that data is accessible, trustworthy, and ready to power everything including, AI models and decision-making at scale.
Role Type: Permanent
Role Location: Bengaluru
Work Hours: Full Time
What will your day look like?
- 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 that enable business use-cases/ outputs, business applications, advanced analytics and AI/ ML outcomes
- Provide high-quality, production-ready data outputs to support 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
- Manage prioritisation, backlog, and execution across multiple teams and delivery streams
- Partner with architecture, governance, AI Portfolio, platform teams, and business stakeholders
- Align engineering delivery to enterprise architecture, data governance, and AI strategy
- Ensure data pipelines and products meet security, privacy, and regulatory requirements
- Drive improvements in engineering efficiency, automation, and delivery performance
- Foster a culture of continuous learning, innovation, and quality improvement
What will you bring?
To grow and be successful in this role, you will ideally bring the following:
- Deep expertise in data engineering, data pipelines, and large-scale data processing
- Strong experience in AI/ML data enablement and integration with engineering workflows
- Proven ability to build and scale data products and reusable engineering assets
- Strong understanding of modern data architectures (data lakes, warehouses, streaming, data mesh)
- Experience with cloud-based data platforms and engineering tools
- Knowledge of DataOps, DevOps, and agile delivery practices
- Strong understanding of data governance, quality, lineage, and security requirements
- Proven leadership of large engineering and delivery teams at scale
- Excellent stakeholder engagement and ability to translate business needs into technical delivery
- Execution excellence at scale, delivering complex data engineering initiatives reliably across multiple teams
- Bridging strategy to delivery, translating data and AI priorities into engineered solutions and assetsEngineering quality and discipline, driving standards, reusability, and sustainable practices
- Master’s degree or PhD degree in Computer Science, Engineering, Actuarial Studies, Data Science or AI with proven, hands on enterprise deployment experience in financial services
- Architecture: deep understanding of modern data lakehouse architecture, data fabric and AI model architecture
- Banking domain: deep understanding of financial data, fraud detection, credit score
So why join us?
ANZ is a place where big things happen as we work together to provide banking and financial services across more than 30 markets. With more than 8,500 people, our Bengaluru team is the bank's largest technology, data and operations centre outside Australia. In operation for over 33 years, the centre is critical in delivering the bank's strategy and making an impact for our millions of customers around the world. Our Bengaluru team not only drives the transformation initiatives of the bank, it also drives a culture that makes ANZ a great place to be. We're proud that people feel they can be themselves at ANZ and 90 percent of our people feel they belong.
We know our people need different things to be great in their role, so we offer a range of flexible working options, including hybrid work (where the role allows it). Our people also enjoy a range of benefits including access to health and wellbeing services.
We want to continue building a diverse workplace and welcome applications from everyone. Please talk to us about any adjustments you may require to our recruitment process or the role itself. If you are a candidate with a disability or access requirements, let us know how we can provide you with additional support.
To find out more about working at ANZ visit https://www.anz.com/careers/ . You can apply for this role by visiting ANZ Careers and searching for reference number 127086.
Job Posting End Date
05/11/2026, 11.59pm, (Melbourne Australia)