Manager - Risk Analytics Engineering

Commonwealth Bank of Australia is hiring a Manager - Risk Analytics Engineering. Level rates it ; you can apply on Commonwealth Bank of Australia.

Level's read on this job

On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
Tools and skills the posting cites include Python, SQL and Git.
Level classifies it as a senior role.
Level lists 192 other open roles at Commonwealth Bank of Australia.
The role was posted in the last few days.

AI in this role

Lead data engineering efforts to build scalable risk analytics products, modern data pipelines, and automation practices.

pythonsqlgit

data-engineeringanalytics-engineeringci-cdcloud-migration

Manager - Risk Analytics Engineering

Build data products and engineering foundations for Retail Credit Risk.
Lead the adoption of modern data engineering, cloud and automation practices.
Shape a growing capability with meaningful customer, risk and regulatory impact.

Do work that matters

Be part of the team that helps CommBank make better decisions. Risk Management partners across the Group to identify, assess and manage risk, protecting our customers, strengthening the bank and enabling sustainable growth. Join a collaborative team where you’ll solve complex challenges and use data, insights and innovation to make a meaningful impact.

The Retail Risk Analytics, Insights & Visualisation team supports Retail Credit Risk through trusted analytics, risk insights and data solutions. We monitor portfolio performance, inform strategic decisions and help the organisation meet its regulatory obligations.

This role presents an opportunity to strengthen and shape the team’s analytics engineering capability. You’ll help establish modern ways of building, testing, deploying and managing analytical data products, creating foundations that allow analysts and risk teams to work more efficiently and confidently.

See yourself in our team

As Manager, Risk Analytics Engineering, you’ll be a hands-on technical leader responsible for designing and delivering scalable data products and analytics engineering solutions.

Working across Risk, Business and Technology, you will:

Design, build and maintain scalable data pipelines, curated data products and transformation frameworks using advanced SQL, Python and modern analytics engineering tools.
Establish reusable data models and engineering patterns that make trusted risk data easier to access, understand and use across teams.
Introduce automated testing, monitoring, documentation and data-quality controls across the analytical product lifecycle.
Improve how analytical assets are developed and deployed through version control, CI/CD, orchestration and repeatable engineering practices.
Contribute to cloud migration and platform modernisation, helping move existing analytical processes towards scalable and maintainable solutions.
Build automation and AI-assisted capabilities that improve analytical productivity while meeting Risk governance and control expectations.
Partner with risk specialists to turn portfolio questions and regulatory requirements into robust technical solutions and decision-ready insights.
Provide technical leadership, coach colleagues and help grow analytics engineering capability across the team.
Success in this role will include delivering reliable data products, reducing manual and duplicated analytical processes, and establishing reusable engineering approaches that can support multiple risk use cases.

We’re interested in hearing from people who:

Brings strong data or analytics engineering experience and enjoy solving complex problems in an environment where reliability, governance and business context matter.

You’ll be comfortable remaining close to the technology while influencing stakeholders and guiding others.

Advanced SQL skills and strong practical Python capability.
Experience designing and delivering production-quality data pipelines, transformation workflows or analytical data products.
Strong knowledge of analytical data modelling, automated testing, monitoring and data-quality controls.
Experience with dbt or a comparable transformation framework.
Experience using cloud-based data platforms, version control, CI/CD and workflow orchestration to build scalable and maintainable solutions.
Ability to translate business, risk and regulatory requirements into effective data engineering solutions and clear, actionable insights.
Demonstrated technical leadership, stakeholder engagement and coaching capability.
A relevant qualification in data science, computer science, engineering, mathematics, statistics or a related discipline, or equivalent practical experience. Experience in credit risk, banking, financial services or another regulated environment would be highly regarded.
Experience in using dashboarding tools along with exposure to AI-assisted tooling, development or machine-learning workflows would be valuable.

If you’re motivated by the opportunity to build modern engineering capability and apply it to meaningful risk challenges, we’d love to hear from you.

Working with us

At CommBank, we're committed to creating an accessible, inclusive and respectful workplace. If you require support or adjustments, please let us know. We welcome applications from people of all backgrounds, and we're particularly committed to making a positive difference for Aboriginal and/or Torres Strait Islander Peoples.

If you're already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you'll need to apply through Sidekick to submit a valid application. We’re keen to support you with the next step in your career.

We're aware of some accessibility issues on this site, particularly for screen reader users. We want to make finding your dream job as easy as possible, so if you require additional support please contact HR Direct on 1800 989 696.

Advertising End Date: 05/11/2026

How we rate this

Manager - Risk Analytics Engineering at Commonwealth Bank of Australia rates 25 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Manager - Risk Analytics Engineering is an open job at Commonwealth Bank of Australia.
Level rates this role AI Level 1 of 4: Little AI.
The role is based in Sydney CBD Area.
The job was posted on October 30, 2026.
Seniority: senior.
Applications are handled by Commonwealth Bank of Australia. Apply on Commonwealth Bank of Australia

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data EngineeringAnalytics EngineeringCI/CDCloud MigrationPythonSQLGit

Questions you could be asked

Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where analytics engineering was part of your work. What did you do?
Tell me about a project where ci/cd was part of your work. What did you do?
Tell me about a project where cloud migration was part of your work. What did you do?
Walk me through how you've used Python in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Data Engineering, Analytics Engineering, CI/CD, Cloud Migration, and Python. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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