Staff Data Engineer

Commonwealth Bank; Melbourne; On-site; AUD 170,000 - 210,000; Full time

Job summary

Commonwealth Bank is seeking a Staff Data Engineer to shape scalable data platforms and data products within Payments Technology. You’ll lead hands-on engineering across batch and streaming pipelines, with AWS, Snowflake and Python driving trusted data services for reuse across the bank.

You’ll mentor engineers, define architecture standards, and collaborate with product, security and data consumers to translate complex requirements into reliable, scalable data solutions that power critical

Qualifications

• Experience with large-scale data platforms and data governance.
• Strong cloud data services and distributed processing knowledge.
• Proficient in Spark, Airflow and AWS Glue.
• Ability to lead architecture decisions and engineering standards.

Responsibilities

• Set technical direction for complex data engineering initiatives and influence architecture and standards across squads.
• Design, build and evolve scalable batch and streaming data pipelines using Spark, Airflow and AWS Glue.
• Build cloud-native data solutions across AWS services (S3, EMR, Glue, Lambda, Redshift, SageMaker).
• Mentor engineers and raise data engineering capability across teams.
• Lead practices across testing, CI/CD, infrastructure-as-code, observability and reliability.
• Establish data quality, resilience, performance and maintainability patterns.

Skills

AWS

Snowflake

Python

PySpark

Airflow

Spark

AWS Glue

Lambda

Redshift

SageMaker

CI/CD

Observability

SQL

Leadership

Tools

Airflow

Spark

Glue

Job description

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.

Working with us:

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