Staff Data Engineer: Big Data, AWS & Snowflake Architect

Commonwealth Bank; Sydney; On-site; AUD 180,000 - 240,000; Full time

Job summary

Commonwealth Bank is seeking a Staff Data Engineer to lead the design and delivery of modern data solutions for Home Buying. You will guide architecture, uplift engineering capability and drive critical technology decisions, while hands-on building on Big Data AWS, Snowflake and dbt.

You will shape data pipelines across the full lifecycle, mentor engineers, and collaborate with stakeholders to deliver meaningful data products with scalable, secure, and production-ready solutions.

Qualifications

• Deep data engineering capability with hands-on coding and leadership
• Experience with enterprise data pipelines and modern data platforms
• Strong understanding of data architecture, governance and security

Responsibilities

• Design, build, test and deploy scalable data solutions across the full development lifecycle
• Lead engineering initiatives and coordinate delivery across data, platform, operations and observability teams
• Review solution designs and architectures, providing practical guidance
• Contribute to governance and risk-aware data platform decisions
• Mentor engineers and uplift data engineering capabilities across teams
• Develop reliable data pipelines and production-ready data products
• Partner with stakeholders to translate business needs into technical data solutions
• Contribute to GenAI-enabled data analytics initiatives

Skills

Python / PySpark

Scala or Java

AWS data engineering

S3

EMR/Spark

Airflow

Iceberg

Snowflake

dbt

Kinesis / MSK

CI/CD

DevSecOps

GenAI tools

Tools

dbt

Snowflake

Job description

Commonwealth Bank is seeking a Staff Data Engineer to lead the design and delivery of modern data solutions for Home Buying. You will guide architecture, uplift engineering capability and drive critical technology decisions, while hands-on building on Big Data AWS, Snowflake and dbt.

You will shape data pipelines across the full lifecycle, mentor engineers, and collaborate with stakeholders to deliver meaningful data products with scalable, secure, and production-ready solutions.