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Commonwealth Bank of Australia

Staff Data Engineer

Commonwealth Bank of Australia is hiring a Staff Data Engineer for a remote role open to applicants in Australia. Level rates it ; you can apply on Commonwealth Bank of Australia.

Level's read on this job

  • Level rates this data engineer role Little AI ●○○○: aI is not part of the work.
  • This is listed as a remote role.
  • The posting mentions SageMaker, AWS and Snowflake among its tools and skills.
  • Commonwealth Bank of Australia has 190 other open roles on Level.
  • Posted in the last few days.

AI in this role

Design and scale cloud data platforms, data products, and distributed pipelines supporting critical payment technologies.

sagemakerawssnowflakepythonsparkairflowredshift
data-engineeringdistributed-systemsci-cdinfrastructure-as-code

Staff Data Engineer – Payments Technology


Sydney or Melbourne location


  • Shape scalable data platforms and engineering standards across one of CommBank’s most critical technology domains.
  • Build trusted data products and pipelines with AWS, Snowflake, Python and modern distributed data technologies.
  • Influence how Payments data is engineered, operated and made available for reuse across the bank.

Do Work That Matters


Payments runs and evolves one of CommBank’s most important customer and operational flows, where resilience, safety and disciplined engineering are fundamental. Within Payments and Enterprise Transformation, the focus is also on connecting platforms, data, controls and transformation so change can be delivered with better outcomes for customers. 

 

As a Staff Data Engineer, you’ll provide hands-on technical leadership for the data platforms, data products and pipelines that support Payments. You’ll solve complex engineering problems at scale, influence architecture and engineering standards across squads, and help create reliable, reusable data capabilities.

 

There is meaningful modernisation underway. Payments has already delivered a priority data product through Marketplace as part of work testing CommBank’s enterprise data model and the patterns needed to scale trusted, reusable data products. 

 

See yourself in our team


You’ll work with engineers, architects, product teams and data consumers to design and evolve modern data capabilities for Payments. Your focus will span cloud data engineering, distributed processing, batch and streaming pipelines, data platform patterns and production reliability.

As a Staff Data Engineer, you will:

  • Set technical direction for complex data engineering initiatives and influence architecture and standards across multiple squads.
  • Design, build and evolve scalable batch and streaming data pipelines, using technologies such as Spark, Airflow and AWS Glue.
  • Build cloud-native data solutions across AWS, including services such as S3, EMR, Glue, Lambda, Redshift and SageMaker.
  • Engineer high-quality data products and help evolve enterprise data platform and data marketplace patterns.
  • Lead engineering practices across testing, CI/CD, infrastructure-as-code, observability and production reliability.
  • Establish patterns for data quality, resilience, performance and maintainability across distributed data workloads.
  • Mentor engineers, support technical decision-making and raise data engineering capability across teams.
  • Partner with Architecture, Product, Security and data consumers to translate complex requirements into pragmatic engineering solutions.

 

We’re interested in hearing from people who:


You’re an experienced data engineer with deep technical capability and a track record of influencing engineering beyond your immediate team. You enjoy solving difficult data problems, setting engineering direction and building platforms that teams can operate confidently at scale.


You’ll bring strong experience across several of the following:


  • AWS data services, particularly S3, EMR, Glue, Lambda, Redshift, SageMaker or comparable cloud technologies.
  • Snowflake, enterprise-scale data platforms, data products or data marketplace patterns.
  • Python and PySpark, with strong experience in distributed data processing.
  • Designing and operating batch and streaming pipelines using technologies such as Airflow, Spark and Glue.
  • CI/CD, automated testing and infrastructure-as-code, with an engineering mindset covering the complete delivery lifecycle.
  • Observability, monitoring and reliability engineering for production data platforms and pipelines.
  • Advanced SQL and strong experience with relational database technologies.
  • Technical leadership across architecture and design, including mentoring engineers and influencing engineering standards across teams.

If this opportunity excites you, apply today.


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. For support please contact 1800 989 696. 

 


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: 06/11/2026

How we rate this

Staff Data Engineer at Commonwealth Bank of Australia rates 20 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.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data EngineeringDistributed SystemsCI/CDInfrastructure As CodeSageMakerAWSSnowflakePython

Also common in data engineer jobs at this level

Pay

Typical data engineer job
$150k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

  1. Tell me about a project where data engineering was part of your work. What did you do?
  2. Tell me about a project where distributed systems was part of your work. What did you do?
  3. Tell me about a project where ci/cd was part of your work. What did you do?
  4. Tell me about a project where infrastructure as code was part of your work. What did you do?
  5. Walk me through how you've used SageMaker in your day-to-day work.

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  • List these exact terms on your resume: Data Engineering, Distributed Systems, CI/CD, Infrastructure As Code, and SageMaker. 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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