About Liberty
Helping people is at the core of who we are. As Australia’s top non-bank lender, we’ve spent decades providing free-thinking and innovative loans and have assisted over 500,000 individuals in achieving financial stability. Our range of flexible, tailored products and our dedication to creating outstanding customer experiences are at the heart of what we do.
We are a collaborative and vibrant community, driven by our core values. Our vision of leading the finance sector with innovative thinking is guided by FLAIR, our five key principles of being Fair, Learning, Accountable, Invested, and Resourceful. These values shape our perspective, interactions with customers, and relationships with one another.
The Opportunity
The Opportunity
You’ll work with a modern Microsoft Fabric and Azure stack, using Python, Terraform, and AI-assisted development to deliver curated data layers that power BI dashboards and intelligent services.
This role is ideal for someone who blends deep technical skills with curiosity, rapid learning, and a drive to create business impact. You’ll be part of a team that values ownership, experimentation, and continuous improvement—and you’ll help shape the future of Liberty’s AI-first data platform.
This role requires a minimum of three days in the office to support collaboration and learning.
What You’ll Be Doing
- Designing and building production-grade data pipelines using Medallion architecture (Bronze → Silver → Gold).
- Developing and deploying Python services on Azure Kubernetes Service (AKS) to support AI and operational workloads.
- Creating curated data layers that serve both Power BI dashboards and AI pipelines (e.g. speech-to-text, NLP).
- Managing infrastructure using Terraform and Liberty’s CI/CD templates for reproducible, scalable deployments.
- Collaborating with Risk, Data Science, and Technology teams to deliver high-impact data products.
- Ensuring data quality through validation, anomaly detection, and automated testing, Support metadata management, data lineage, and discoverability.
- Supporting semantic modeling and discoverability for BI and AI consumption.
- Implement monitoring and observability for data pipelines.
- Translating business goals into technical solutions that drive decisions and outcomes.