2 weeks ago

Staff Data Engineer (AWS, Postgres)

Commonwealth Bank

Sydney

2 weeks ago

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CommBank is seeking a Staff Data Engineer to provide technical leadership in designing, delivering, and modernizing cloud-native data platforms within Financial Services & Control Technology. The role focuses on migrating legacy Microsoft SQL Server platforms to AWS-native services and requires deep expertise in data engineering, AWS, and technical leadership.

AI-enabledHybridFull-timePrincipalSQLPostgreSQL

Staff Data Engineer (AWS, Postgres)

Apply

AI-enabledHybridFull-timePrincipalSQL

Salary

Not specified

Work Location

Sydney, New South Wales, Australia, AU

Work Model

Hybrid

Employment Type

Full-time

Experience Level

Staff

Core Qualifications

Technical (Must-have)

SQLPostgreSQLAWSAurora PostgreSQLAWS GlueAmazon RedshiftAmazon S3AthenaLambdaEMRPythonPySparkETLELTGitCI/CDDevOpsAgileData GovernanceData LineageMetadata ManagementData QualityData ModellingDatabase Performance OptimizationCloud Data ArchitectureInfrastructure as CodeAutomation

Soft Skills

Technical LeadershipMentoringCommunicationCollaborationProblem Solving

Preferred Qualifications

Technical (Nice-to-have)

AWS DMSAWS Schema Conversion ToolAmazon QuickSightSnowflakePower BITableauAWS Certified Data Engineer Associate

Key Responsibilities

•Lead the design, delivery and ongoing evolution of a scalable, secure and cost-effective cloud-native data platform supporting Product Control
•Drive the modernisation of legacy data, reporting and analytics capabilities, transitioning from Microsoft SQL Server, SSIS, SSRS and SSAS to AWS-native services including Aurora PostgreSQL, AWS Glue, Amazon Redshift, QuickSight and Snowflake.
•Design, build and optimise enterprise-scale data products, databases and data pipelines that deliver trusted, high-quality data assets for reporting, analytics and regulatory requirements.
•Lead technical decisions and actually do data modelling, database design, performance optimisation and cloud data architecture, ensuring solutions are scalable, resilient and aligned with enterprise standards.
•Establish and enhance automated data quality, reconciliation, monitoring and operational controls to support platform reliability and governance outcomes.
•Drive adoption of modern engineering practices including CI/CD, Infrastructure as Code, platform automation and AI-assisted engineering capabilities to improve delivery velocity and quality.
•Provide hands-on technical leadership, mentoring and engineering oversight, reviewing designs and implementations while uplifting capability across the Data Engineering practice.
•Partner with architects, engineers, data consumers, business stakeholders and delivery teams to successfully modernise, operate and continuously enhance the Product Control data platform.
•Support strategic platform initiatives through all stages of delivery, including design, engineering, testing, reconciliation, migration, cutover, production support and ongoing feature development.

Staff Data EngineerAWSPostgreSQLData EngineeringCloudFinancial ServicesHybridTechnical LeadershipData PlatformMigration

Core Qualifications

Technical (Must-have)

Soft Skills

Technical LeadershipMentoringCommunicationCollaborationProblem Solving

Key Responsibilities

•Lead the design, delivery and ongoing evolution of a scalable, secure and cost-effective cloud-native data platform supporting Product Control

•Drive the modernisation of legacy data, reporting and analytics capabilities, transitioning from Microsoft SQL Server, SSIS, SSRS and SSAS to AWS-native services including Aurora PostgreSQL, AWS Glue, Amazon Redshift, QuickSight and Snowflake.

•Design, build and optimise enterprise-scale data products, databases and data pipelines that deliver trusted, high-quality data assets for reporting, analytics and regulatory requirements.

•Lead technical decisions and actually do data modelling, database design, performance optimisation and cloud data architecture, ensuring solutions are scalable, resilient and aligned with enterprise standards.

•Establish and enhance automated data quality, reconciliation, monitoring and operational controls to support platform reliability and governance outcomes.

•Drive adoption of modern engineering practices including CI/CD, Infrastructure as Code, platform automation and AI-assisted engineering capabilities to improve delivery velocity and quality.

•Provide hands-on technical leadership, mentoring and engineering oversight, reviewing designs and implementations while uplifting capability across the Data Engineering practice.

•Partner with architects, engineers, data consumers, business stakeholders and delivery teams to successfully modernise, operate and continuously enhance the Product Control data platform.

•Support strategic platform initiatives through all stages of delivery, including design, engineering, testing, reconciliation, migration, cutover, production support and ongoing feature development.