Lead, Risk Analytics Engineering & Data Products

Commonwealth Bank Of Australia; Western Australia; On-site; AUD 160,000 - 200,000; Full time

Job summary

Commonwealth Bank of Australia invites applications for a Manager - Risk Analytics Engineering. You will lead the design and delivery of scalable data products and analytics engineering solutions across Risk, Business and Technology teams.

You will build robust data pipelines using SQL, Python and modern tooling, establish reusable data models, and drive automated testing, monitoring and data quality controls throughout the product lifecycle.

Qualifications

• Advanced SQL and Python proficiency.
• Experience delivering production-quality data pipelines or analytic data products.
• Knowledge of analytical data modelling, automated testing, monitoring and data quality controls.
• Experience with dbt or comparable transformation framework.
• Experience using cloud-based data platforms, version control, CI/CD and workflow orchestration.

Responsibilities

• Design, build and maintain scalable data pipelines and data products.
• Establish reusable data models and engineering patterns for trusted data.
• Introduce automated testing, monitoring, documentation and data-quality controls.
• Improve analytics asset development and deployment with CI/CD and orchestration.
• Contribute to cloud migration and platform modernization.
• Build automation and AI-assisted capabilities for productivity and governance.
• Partner with risk experts to translate portfolio questions into technical solutions.
• Provide technical leadership and coach teammates.

Skills

Advanced SQL

Python

dbt

Cloud platforms

CI/CD

Orchestration

Data modelling

Automated testing

Education

Data science / Computer science / Engineering / Mathematics degree

Tools

dbt

Cloud platforms

Version control

CI/CD

Orchestration

Dashboarding tools

AI tooling

Job description

Commonwealth Bank of Australia invites applications for a Manager - Risk Analytics Engineering. You will lead the design and delivery of scalable data products and analytics engineering solutions across Risk, Business and Technology teams.

You will build robust data pipelines using SQL, Python and modern tooling, establish reusable data models, and drive automated testing, monitoring and data quality controls throughout the product lifecycle.