Start your career in Data Engineering through Macquarie's structured two-year Graduate Program, where you'll gain hands-on experience building the data platforms that power reporting, analytics and AI across the business.
Working alongside experienced Data Engineers, you'll help build modern cloud-based data solutions using Microsoft Fabric while applying and strengthening your AI, Data, Python & SQL skills. You'll contribute to real projects from day one, helping design data pipelines, support analytics solutions and solve meaningful business challenges.
With structured mentoring, industry certifications, business rotations and ongoing learning, you'll develop the technical and professional skills needed to build a successful career in Data Engineering. As the platform evolves, you'll also have the opportunity to contribute to emerging AI and automation initiatives, gaining exposure to technologies shaping the future of data.
Australia's #1 Great Place To Work in Technology, 2026.
We have been awarded Australia's #1 Great Place to Work 2025 for the second year running!
We're Great Place to Work Certified 2023, 2024 and 2025.
For the third year in a row, we have been named a Global Winner of the 2026 Gallup Exceptional Workplace Award!
We're the #1 Managed Services Cloud business in Australia.
We have the highest Net Promoter Score on the ASX, the World's best customer experience & crowned in 2020 at the World Communications Awards.
You’ll make an impact: Enjoy being part of a driven team with a collaborative culture that values decision-makers and action.
We Invest in you: Accelerate your career through our learning and development opportunities - think Gallup strengths-based training, defined career pathways and fantastic internal mobility opportunities across the group.
Participate in a structured two-year Graduate Program with mentoring, certifications and business rotations.
Build your understanding of the business by supporting BI requests, troubleshooting dashboards and learning the Microsoft Fabric platform during your first few months.
Learn to build and maintain modern cloud-based data solutions using Microsoft Fabric.
Apply and strengthen your Data Engineering, Python, SQL and GitHub skills while working on real engineering projects.
Support and enhance Power BI dashboards, datasets and scheduled reporting.
Assist with building data pipelines that transform and prepare data for reporting and analytics.
Contribute to platform migration projects as the business transitions reporting and analytics to Microsoft Fabric.
Work alongside experienced Data Engineers to deliver trusted data products for the business.
Partner with stakeholders to understand business requirements and translate them into data solutions.
Apply best practices for data quality, documentation, governance and security.
Support users of the data platform by responding to queries and helping improve self-service analytics.
Continuously learn new technologies and engineering practices through certifications, mentoring and hands-on project work.
Recently completed (or are about to complete) a degree in Data Science, Computer Science, Information Technology, Software Engineering, Business (Data Analytics, Information Systems or similar), Mathematics, Statistics or a related discipline.
Passionate about technology, data and solving real-world business problems. Exposure to both Python and SQL through university, personal projects or internships.
Experience using GitHub or another version control tool through university or personal projects is highly regarded.
Curious, proactive and eager to learn new technologies, ask questions and continuously develop your skills.
Strong analytical and problem-solving skills with great attention to detail.
Enjoy collaborating with others and communicating ideas clearly.
Excited to build a long-term career in Data Engineering, analytics and emerging AI technologies.
Experience with Power BI, Microsoft Fabric or cloud platforms is advantageous but not essential.
If this excites you, apply now, we'd love to hear from you!
