General Manager Data & AI Engineering Delivery

Anz · Banking & Financial Services

Bengaluru, India
On-site
Posted today
Apply by 5 Nov
Data & AI

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 assets

Engineering 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)

Apply on Anz