arrow_back Back to Dashboard search Browse Jobs
Commonwealth Bank logo

Commonwealth Bank

Staff Data Engineer

🗓️ Posted 2026-08-10 Sydney, New South Wales, Australia Full-time On-site ICT

Company shared salary

NA

Market rate

A$10,833–A$15,000/mo (A$129,996–A$180,000/yr)

Based on similar roles (title + domain + location).

About the Company

Staff Data Engineer - Customer Channels & Data Business Banking Technology Shape the future of customer engagement through data, AI and intelligent decisioning. Influence data architecture, engineering standards and platform strategy across Business Banking. Experiment with and scale Generative AI and agentic AI capabilities powered by modern data platforms. Do work that matters At CommBank, we're transforming how Business Banking customers and colleagues engage with the bank through data-driven experiences, intelligent insights and emerging AI capabilities. As a Staff Data Engineer, you'll play a critical role in designing and building the data platforms, products and pipelines that power customer engagement, CRM experiences, operational intelligence and AI-enabled solutions across our Customer Channels & Data domain. You'll have the opportunity to work with emerging Generative AI and agentic AI capabilities, helping build the trusted data foundations required to deliver intelligent customer and colleague experiences at scale. Working closely with engineers, product teams, architects, analysts, data scientists and AI specialists, you'll influence platform strategy, engineering practices and technical direction while remaining hands-on with technology and delivery. See yourself in our team Business Banking Technology executes the Technology Strategy across Business Banking through world-leading application of technology and operations. We partner closely with the business to

Responsibilities

  • ● Design, build and evolve scalable cloud-native data products, platforms and pipelines.
  • ● Lead technical design and engineering decisions across data architecture, ingestion, transformation and consumption patterns.
  • ● Build trusted data assets that power customer engagement, reporting, analytics and AI-enabled experiences.
  • ● Establish engineering standards and reusable patterns for data integration, quality, governance and security.
  • ● Champion modern engineering practices including DevSecOps, CI/CD, automation and observability.
  • ● Drive platform efficiency through automation, AI-assisted engineering and continuous improvement.
  • ● Mentor data engineers and help uplift technical capability across the team.
  • ● Partner with product, architecture, risk and business stakeholders to deliver meaningful customer and business outcomes.
  • ● We're interested in hearing from people who have
  • ● Strong experience designing, building and operating large-scale data platforms and data products.

Requirements

  • ● Proven expertise in data architecture, data modelling and distributed data ecosystems.
  • ● A passion for engineering excellence, automation and continuous improvement.
  • ● Strong stakeholder engagement and collaboration skills.
  • ● Technical skills
  • ● We use a broad range of tools, languages, and frameworks. We don't expect you to know them all but experience or exposure with some of these (or equivalents) will set you up for success in this team;
  • ● Extensive experience in designing, building, and delivering enterprise-wide data ingestion, data integration and data pipeline solutions
  • ● Strong Data Architecture expertise including different data modelling techniques and design patterns (conceptual, logical, physical, semantic is preferred)
  • ● Strong knowledge of data governance such as data lineage, technical metadata, data quality and reconciliation
  • ● Ability to drive platform efficiency through automation and AI capabilities
  • ● AWS Data Stack: EMR, Glue, Redshift, Athena, S3, Lambda, ECS
  • ● Data Orchestration & Pipelines: Airflow, Dataform
  • ● Data Formats & Modelling: Iceberg, JSON, XML, CSV, Data Modelling
  • ● Programming & DevOps: Python, SQL, Git, GitHub Actions, Team City, Jenkins, Octopus Unix shell scripting
  • ● ETL & Ingestion: File ingress/egress solutions in AWS
  • ● Security and Observability: DevSecOps, Artifactory, Observability tooling
  • ● Testing & Automation: test automation frameworks, Jupyter Notebooks
  • ● Familiarity with data warehousing and build experience in Teradata, Oracle
  • ● Familiarity and experience with Agile processes
  • ● AWS Data Engineer Associate certification
  • ● If this sounds like you, apply today