At a Glance
- Tasks: Lead the creation of data products and modern analytics solutions for Retail Credit Risk.
- Company: Join CommBank, a leader in banking with a focus on innovation and collaboration.
- Benefits: Enjoy competitive pay, inclusive culture, and opportunities for professional growth.
- Other info: Be part of a diverse team committed to making a positive difference.
- Why this job: Make a real impact by shaping risk analytics and improving decision-making processes.
- Qualifications: Strong experience in data engineering, SQL, Python, and analytical problem-solving.
The predicted salary is between 56700 - 69300 $ per year.
- 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 Comm Bank 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
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Manager - Risk Analytics Engineering in Sydney employer: CommBank
CommBank is an exceptional employer that prioritises employee growth and inclusivity, making it a fantastic place for the Workforce Effectiveness Lead role. With a strong focus on innovation and collaboration, employees are encouraged to develop their skills in a supportive environment that embraces diversity and fosters meaningful contributions to the future of work. Located in a vibrant community, CommBank offers unique opportunities to engage with cutting-edge technologies and shape the workforce landscape while enjoying a culture that values respect and accessibility.
