Responsibilities:

• In this role, I lead how large-scale data systems are designed and managed within one of Australia’s major banks. I look after a team of over 20 Data Engineers and Analysts, focusing on building cloud-based platforms that make data reliable, compliant, and useful for everyday decision-making.
• Much of my work involves modernising old systems and moving them into automated, AWS-based environments. I’ve led the creation of data pipelines and lakehouse setups that give teams access to consistent, traceable information. These data assets now support more than 10 business areas and meet the strict audit and validation standards expected in a regulated environment.
• Helping global teams lift their technical capability through mentoring and knowledge-sharing that built consistency and confidence
• Delivering a large-scale regulatory data asset that strengthened compliance readiness across multiple business areas
• Designing proactive data-quality frameworks that reduced operational risks and improved reporting reliability
• Overseeing the shift from legacy systems to a cloud-based data mesh, improving scalability and automation
• Contributing to customer-focused projects that made financial insights clearer and easier to access
• I also play an active role in helping hundreds of Data Engineers build their skills and technical confidence through structured mentoring and learning. The combination of technical depth and people leadership has allowed me to guide projects from concept through implementation while maintaining a strong focus on long-term value.

Responsibilities:

• During this period, my focus was on building and maintaining the bank’s enterprise data warehouse environment and improving how information moved through large systems. The work was technical and detail-heavy. I designed data pipelines, developed ETL processes, and ensured production systems remained stable and auditable.
• I worked extensively with SQL Server, SSIS (BIML), and Microsoft Reporting Services to deliver data solutions that supported business reporting and analytics. I also created data models and Qlik Sense dashboards that made information easier for business teams to access and interpret. To improve deployment consistency, I helped implement the Bamboo continuous integration framework, which reduced manual errors and sped up release cycles.
• Developing data assets and financial data pipelines that supported major compliance and reporting programs
• Delivering engineering projects focused on assurance, remediation, and financial data extraction for audits and acquisitions
• Designing a commercial data platform that improved how customer acquisition and retention were tracked
• Creating a .NET Windows application that allowed teams to manage business hierarchies more efficiently
• This role grounded me in the discipline of data engineering, such as version control, deployment, testing, and recovery, while also teaching the importance of accuracy in environments where small data errors can have wide impacts. It set the groundwork for how I now approach the design and management of complex data systems.

Responsibilities:

• I managed the design and delivery of data warehouse systems that supported critical customer and business insights. I worked hands-on with T-SQL and SSIS to develop and maintain high-performing pipelines and reporting environments to ensure that data used across the business was accessible and reliable.
• Alongside the technical work, I looked after database configuration and system administration. I was also involved in recruiting new members, guiding their onboarding, and supporting their technical growth through mentoring.

Responsibilities:

• I started out at Esanda, which later became part of ANZ, where my focus was on making data more useful for people on the frontline. Back then, most reporting was manual, so I helped shape the early data warehouse environment that made information easier to access and interpret.
• A lot of my work was hands-on, like building small tools to help staff understand why customers were calling, creating reports that showed where service bottlenecks were happening, and refining how escalations were tracked.
• It was a mix of technical problem-solving and process improvement, and it gave me an early appreciation of how data could directly influence both customer experience and operational decisions.