You are passionate to stay ahead of the latest AWS Cloud, Gen AI, Data Lake, and Data Mesh technologies.
We are one of the largest and most advanced Data Engineering teams in the country.
Together we can build state-of-the-art data solutions that power seamless experiences for millions of customers.
Do work that matters:
As a Staff Data Engineer with expertise in software development / programming and a passion for building data-driven solutions, you are ahead of trends and work at the forefront of AWS Cloud, Data Mesh and AI technologies.
See yourself in our team:
Join the Business Banking (BB) Technology team at CommBank, where we are driving innovation through Digital and Gen AI platforms that empower our Business Bank customers.
Our team plays a pivotal role in delivering secure, reliable, and actionable data products. These assets support strategic decision-making, risk management, and customer success. This is driven by critical data assets which is supported by the Data Engineering teams within the BB Technology who are responsible for ingesting data, creating ESDM aligned Data Products and creating reports which will help business produce strategies.
We are also interested in hearing from people who:
Think AI-first and are passionate about solving problems with intelligent data solutions.
Have a strong learning mindset and thrive in collaborative environments.
Champion a culture of quality, openness, and continuous improvement.
Design and build next-gen data platforms and pipelines using Python, PySpark, or Scala.
Integrate data from diverse sources into centralised lakes and cloud platforms.
Create technology blueprints and engineering roadmaps for long-term transformation.
Ensure data security, governance, and compliance.
Deliver end-to-end solutions that meet business needs and minimise risk.
Build high-quality, scalable data products from scratch.
Communicate effectively with stakeholders and contribute to team-wide engineering practices.
Define and evolve shared semantic models and metric definitions to ensure consistent meaning and reusable data across products and domains.
Drive adoption of catalogues, glossaries, and stewardship practices that promote discoverability, accountability, and self-service.
Embed policy-as-code for data access, classification, and retention ensuring compliance with internal and regulatory standards.
Implement automated testing, observability, and end-to-end lineage to improve data trust, traceability, and incident resolution speed.
Key Skills & Experience:
AWS Certified Data Engineer Associate with demonstrable experience in Data Engineering.
Data Processing: Strong expertise in Python, PySpark, SQL, Spark, Scala, and distributed data processing.
Experience in AWS data platforms (Glue, Lambda, Redshift, Athena, Kinesis, EMR).
Data Governance & Security: Experience with AWS DataZone, Lake Formation, IAM, encryption.
Experience in using AI Powered coding Assistants like Cline, Roo and Aider.
Marketplace & APIs: Exposure to AWS Marketplace, API Gateway, and data monetization strategies.
Automation & CI/CD: Experience with Terraform, CloudFormation, GitOps, and serverless frameworks.
Performance Optimisation: Ability to fine-tune ETL jobs, query performance, and cost efficiencies.
Experience with Snowflake, or Apache Iceberg.
Knowledge of data product thinking and data mesh principles.
Working with us
Whether you are passionate about customer service, driven by data, or called by creativity, a career with CommBank is for you.
We support our people with the flexibility to balance where work is done with at least half your time each month connecting in our Sydney or Melbourne office. We also have many other flexible working options available including changing start and finish times, part-time arrangements and job share to name a few.
If this sounds like you, apply now!
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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