Who is Shift?
At Shift, we’re business specialists dedicated to helping Australian SMEs take control of their cashflow, streamline trade terms and choose the right financial products.
We believe Australian businesses are the driving force behind our economy and are core to our communities. That’s why our business expertise, focus on relationships, and market-leading technology is at the core of everything we do. We’ve helped solve the credit and payment pain points for more than 30,000 businesses, providing over $6 billion in aggregate funding.
Our unique approach to product innovation combined with our collaborative culture means you can build your career in a supportive environment. You’ll be joining a diverse team of over 300 people who are always looking to deliver better outcomes for Australian businesses.
About the role:
Shift is at an exciting point in its data journey. We're building out a centralised, high-performing data team and this role sits right at the heart of it. As a Data Engineer at Shift, you'll work alongside our Senior Data Engineer to maintain and evolve our Azure-based data platform - while contributing to a significant uplift in our data model as we build towards the next generation of our credit decisioning capability. This isn't a role where you'll be heads-down in isolation. You'll work closely with analysts, data scientists and business stakeholders across a flat, fast-moving organisation where your work is visible and your contribution matters.
What you'll do:
Build and maintain robust ELT pipelines for enterprise-grade data integration across Shift's lending, product and analytics operations
Contribute to the evolution of our data architecture, including schema design, metadata management and governance standards through Unity Catalog
Apply data quality and consistency standards across pipelines and systems
Manage and optimise databases, including query tuning and storage performance
Partner with analysts, data scientists and engineers to translate business requirements into working data products
Develop modular, reusable scripts and tools to support automation and scalability
Identify and contribute to opportunities to build AI-augmented data workflows that scale analytical output across the business
What you'll bring
3-5 years experience in a data engineering or related role
Hands-on experience building ELT pipelines using Azure Data Factory and Azure Databricks
Strong SQL and Python skills, including query optimisation and complex transformations
Working knowledge of dimensional modelling, Delta Lake and medallion architecture
Practical experience with Azure SQL Database, Azure Data Lake Storage Gen2 and Azure Key Vault
Experience automating workflows using Azure Functions and CI/CD pipelines in Azure DevOps
Comfortable using AI coding assistants (e.g. GitHub Copilot, Claude) to accelerate your work and curious about what's next
A collaborative working style - you bring problems to the team, not just solutions to your manager
Clear communicator who can translate technical concepts for non-technical stakeholders
Key benefits:
Collaborative teams – a flat structure means everyone can learn from colleagues and senior leaders around the business.
Be involved – come together with all of your colleagues every 100 days to share the product and technology roadmap and business strategy.
Flexible working environment – we’re headquartered in North Sydney with state-based workplaces and offer a flexible work policy.
Family support – industry leading 26 weeks paid parental leave.
Purpose built spaces within our office – designed for collaboration, brainstorming, socialising, and focused work.
Range of benefits supporting your physical, psychological and financial wellbeing. From a day off on your birthday to excellent end of trip facilities.
#LI-Hybrid