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Early. Similar jobs usually come down between day 6 and day 47.
From 1,409 similar postings that came down. Coming down is not always a hire.
Manager - Risk Analytics Engineering
Sydney CBD Area
Actively hiring, first seen by us 5 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingBuild and maintain data pipelines, curated data products and transformation frameworks
Establish reusable data models that make trusted risk data easier to use
Introduce automated testing, monitoring and data-quality controls
Improve development and deployment via version control, CI/CD and orchestration
Partner with risk specialists to turn portfolio and regulatory needs into technical solutions
From the employer’s posting
Design, build and maintain scalable data pipelines, curated data products and transformation frameworks
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.
Partner with risk specialists to turn portfolio questions and regulatory requirements into robust technical solutions and decision-ready insights.
Posting record
Report an errorActively hiringFirst seen by us 5 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 30, 20265 days ago
- Recorded sightings
- 6
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Commonwealth Bank is hiring
18 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down quickly
- 22% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- dbt
Where the posting names them
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.
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.
Your next step
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About the role
We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
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.
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Sydney CBD Area
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