Staff Data Engineer (Big Data, AWS and Snowflake)

CommBank; Sydney; On-site; AUD 140,000 - 190,000; Full time

Job summary

CommBank is seeking a Staff Data Engineer to design and deliver modern data solutions for Home Buying. You will shape architecture, uplift engineering capability and influence critical technology decisions while building with Big Data AWS, Snowflake and dbt.

You will lead technical governance, mentor engineers, and partner with stakeholders to deliver secure, production-ready data products and insights. Strong SQL and Python/ PySpark skills are essential.

Qualifications

• Experience building enterprise data pipelines using SQL and code (Python/Scala/Java).
• Hands-on AWS data engineering with S3, EMR/Spark, Airflow, Iceberg and Glue.
• Strong knowledge of Snowflake in production environments.

Responsibilities

• Design, build, test and deploy scalable data solutions across the full lifecycle.
• Lead engineering initiatives and coordinate delivery across data, platform, operations, and observability teams.
• Review designs and architectures, guiding decisions per engineering standards.

Skills

Data pipelines

SQL

Python

PySpark

Scala

Java

AWS

Snowflake

dbt

GenAI / AI engineering

Tools

Airflow

S3

EMR/Spark

Iceberg

AWS Glue

Job description

Staff Data Engineer (Big Data, AWS and Snowflake)

Staff Data Engineer (Big Data, AWS and Snowflake)

Lead the design and delivery of modern data solutions supporting Home Buying.

Shape architecture, uplift engineering capability and influence critical technology decisions.

Build with Big Data AWS, Snowflake and dbt as CommBank modernises its data estate.

Do Work That Matters

Be part of the team at the heart of how CommBank serves Australia. Join a team where you’ll have a positive impact on customers’ lives, strengthen local communities and build a rewarding career.

As a Staff Data Engineer, you’ll contribute directly to the delivery of data products and solutions for Home Buying while providing technical leadership across the engineering practice. You’ll combine hands-on engineering with broader technical leadership, helping the team build, test and deploy production data products and solutions while influencing architecture, governance, and engineering standards. You’ll also support the modernisation of our data domain as we evolve our existing Big Data AWS-based platforms and increase our use of Snowflake and dbt.

See yourself in our team

Data powers the experiences we create for millions of customers. You’ll join a collaborative engineering environment where you can solve complex problems, support other engineers and help shape the technology that underpins important customer experiences.

In this role, you will:

• Design, build, test and deploy scalable data solutions across the full engineering development lifecycle.
• Lead engineering initiatives and coordinate delivery across data, platform, operations, and observability teams.
• Review solution designs and architectures, providing practical guidance aligned with engineering standards and strategy.
• Contribute to technical governance, helping teams make sound decisions about architecture, implementation, risk and adoption.
• Support engineers when they encounter complex technical challenges and mentor them to build their capability.
• Develop reliable data pipelines and data products that are secure, maintainable and production-ready.
• Partner with technical and business stakeholders to understand business requirements, provide and assess different technical data solutions, and deliver meaningful outcomes.
• Contribute to engineering recruitment activities, including technical interviews and the consistent application of hiring standards, and uplift our data engineering resource capabilities.
• Contribute to how we will be using GenAI to improve our ways of working, deliver better data analytics and insights, and increase productivity.

We’re interested in hearing from people who:

Bring deep data engineering capability, sound technical judgement and the confidence to lead through influence. You’ll be comfortable remaining hands-on while guiding solution decisions, supporting other engineers and collaborating across organisational boundaries.

We use a broad range of technologies and do not expect you to know every tool. Experience with several of the following, or comparable technologies, will help set you up for success:

• Strong experience designing and delivering enterprise data pipelines using complex SQLs and programming languages such Python / PySpark, Scala or Java.
• Practical AWS data engineering experience, particularly with services such as Amazon S3, EMR/Spark, Airflow, Iceberg, and AWS Glue.
• Strong experience using Big Data technologies such as Spark, Hadoop, Hive, Iceberg, Sqoop, Kinesis or MSK/Kafka, and related processing patterns.
• Experience using Snowflake in a production environment and an understanding of how data solutions are designed and built on the platform.
• Experience with dbt or comparable data transformation frameworks.
• Experience leading architecture and design reviews while balancing delivery, risk, security, maintainability and cost.
• Demonstrated ability to mentor engineers and lead initiatives involving multiple teams and stakeholders.
• Understanding of modern engineering practices, including source control, CI/CD, automated testing, DevSecOps and continuous integration and delivery.
• Experience in using AI Engineering frameworks and tools, like Claude, LangGraph, LangChain, Codex, ChatGPT, Copilot, etc.

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 ***.