Staff Data Engineer

About the role

Staff Data Engineer You are passionate about solving complex problem with the latest tech We're the largest and most advanced Data Engineering teams in the country. Together we b uild tomorrow's bank with world class engineering Do work that matters We're building tomorrow's bank today - and that takes creative, diverse engineers who want to push boundaries, work at scale, and solve complex data‑driven challenges that matter. As a Staff Data engineer with expertise in data engineering, you'll work at the forefront of regulatory reporting technology, delivering critical solutions that support regulatory compliance and the Bank's global ambitions. If you're motivated by scale, complexity, and purpose this role is built for you. See yourself in our team This role sits within the Capital, Climate & Regulatory Reporting Crew, where we design and deliver technology solutions that ensure the CBA Groups compliance to Regulatory capital, Climate disclosures and Regulatory reporting through the design, development, maintenance and optimization of the regulatory calculations and solution. As a Staff Data Engineer, you'll be an integral member of our Engineering practice. Your role will be to lead and guide a team of engineers collaborating across a wide range of business and technical stakeholders to deliver a transformative and strategic data platform initiative to meet current and future crew requirements. We are seeking an outstanding staff Data Engineer to join our team and help shape the reporting solutions that we are building. Roles & Responsibilities Design, build and deliver a new cloud data solution to transform our international regulatory reporting requirements Lead the design and delivery of cost-effective, scalable data solutions aligned with strategic goals that meet performance, security and operational requirements. Drive solution architecture decisions ensuring alignment with enterprise architecture principles and business priorities Engineer robust data product assets and pipelines in AWS (S3, Glue, Iceberg, Kinesis, Airflow, Sagemaker, Redshift) that integrate with other applications including SaaS reporting applications eg. Axiom Provide technical data governance and risk management, Lead a team of data engineers providing technical guidance, reviewing work and mentoring team members to deliver high-quality data products Define and implement engineering standards, including data modelling, ingestion, transformation, and egression patterns and reviews Collaborate across teams to ensure secure, efficient, and well-documented solution. Learn and contribute to continuous improvement initiatives within the team. We are interested in hearing from people who Have strong experience in Data Engineering using Agile practices and DevSecOps Are experienced in designing, building and delivering "greenfield" data solutions in AWS Cloud using cloud native technologies that produce data products or data assets with proper data quality assurance and security controls. Are passionate technology leaders, can mentor and build a good community of engaged and curious engineers Have strong solution design capabilities, consistently driving cost effective and technologically feasible solutions, while steering solution decisions across the group, to meet both operational and strategic goals is essential. Have excellent verbal and written communication skills Have an ability to engage, manage internal stakeholders and external suppliers Have a problem-solving mindset with a focus on automation and continuous process improvement Skills Required We use a broad range of tools, languages, and frameworks. We don't expect you to know them all but experience or exposure with some of these (or equivalents) will set you up for success in this team; Extensive experience in designing, building, and delivering enterprise-wide data ingestion, data integration and data pipeline solutions Strong Data Architecture expertise including different data modelling techniques and design patterns (conceptual, logical, physical, semantic is preferred) Strong knowledge of data governance such as data lineage, technical metadata, data quality and reconciliation Ability to drive platform efficiency through automation and AI capabilities AWS Data Stack: EMR, Glue, Redshift, Athena, S3, Lambda, ECS Data Orchestration & Pipelines: Airflow, Dataform Data Formats & Modelling: Iceberg, JSON, XML, CSV, Data Modelling Programming & DevOps: Python, SQL, Git, GitHub Actions, Team City, Jenkins, Octopus Unix shell scripting ETL & Ingestion: File ingress/egress solutions in AWS Security and Observability: DevSecOps, Artifactory, Observability tooling Testing & Automation: test automation frameworks, Jupyter Notebooks Familiarity with data warehousing and build experience in Teradata, Oracle Experience in visualisation tools such as PowerBI, Tableau Familiarity and experience with Agile processes AWS Data Engineer Associate certification If this sound

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