Chapter Lead
Senior Engineering Manager / Chapter Lead (Data Engineering)
- Lead data engineering capability for a critical data platforms crew within Economic Crime
- Shape modern data platforms, controls and engineering practices across a large-scale data environment.
- Help CommBank advance future-ready technology, data, AI and GenAI capabilities.
Do Work That Matters
See yourself in our team
The newly established Data Platforms Crew within the Economic Crime function plays a critical role in helping the Group understand, monitor and manage economic and financial crime risk by delivering trusted data, reporting, analytics and insights that support risk governance, regulatory obligations, operational effectiveness and executive decision-making.
The role will include setting the strategic direction for the data platform and provide analytics and insights which will support the transformative three-year vision of the bank in order to combat financial crime detection and prevention.
Key Responsibilities:
- Solution designing, architecture, coding, technical reviews, platform uplift, troubleshooting
- Lead, coach and develop data engineers across multiple data squads, supporting wellbeing, capability uplift and strong performance outcomes.
- Guide the design, delivery, testing and maintenance of trusted data products, pipelines, reporting solutions, dashboards and analytical datasets.
- Drive uplift towards full-stack data engineering, reducing handoffs and improving how engineers work across requirements, build, testing, controls and operations.
- Partner with the Crew Tech Lead, Financial Crime Compliance, Risk, Operations, Technology, Data Governance and enterprise business teams to align delivery with strategic priorities, technology KPIs and OKRs.
- Strengthen data quality, lineage, reconciliation, monitoring, observability, automation and reporting controls.
- Help modernise financial crime technology, data and reporting capabilities as part of the broader economic crime transformation agenda.
- Champion DevSecOps, platform health, vulnerability reduction, operational resilience and secure, scalable engineering practices.
- Support the team's transition from legacy big data and warehouse technologies toward cloud, AWS data services, Snowflake and AI-enabled ways of working.
We’re interested in hearing from people who
We know great candidates may not meet every requirement listed below. If this opportunity excites you and you believe your experience could add value, we'd love to hear from you.
- Proven experience in solution designing, architecture, coding, technical reviews, platform uplift, troubleshooting
- Experience in leading, coaching and developing data engineering teams.
- Strong experience with AWS data services and modern cloud data engineering practices.
- Experience designing and leading large-scale data lakes, data warehouses, data pipelines or analytics platforms.
- Strong understanding of data quality, lineage, reconciliation, control frameworks, assurance and auditability.
- Experience working in complex enterprise, financial services, risk, compliance or regulated environments.
- Knowledge of DevSecOps, observability, vulnerability reduction, platform health, automation and technology OKRs.
- Exposure to big data and data platform technologies such as Spark, Hadoop, Hive, Teradata, SQL, PL/SQL, Snowflake, AWS Glue or related platforms.
- Interest or experience in AI, ML, AI-powered engineering or managing data to support AI systems would be highly regarded.
Working with us
Not included in the source posting: what you'll do, qualifications, benefits.
Skills
Who can apply
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