Senior Software Engineer, Cloud and Analytics platform

About the role

Join our development team and play a key role in our expanding Engineering Services function. You’ll help enhance our innovative analytics and rapid delivery platform as we digitize and modernize the Commodities and Global Markets platforms and applications. Leveraging cutting-edge technologies, you’ll enable the business to scale and seize new opportunities with agility. We are a global financial services group operating in 30 markets with 57 years of unbroken profitability. At Macquarie, you’re empowered to shape a career that is fulfilling and creates value. You will bring your insights and expertise to the task at hand and feel supported as you make your own kind of impact for a better future.

Responsibilities

You’ll combine hands-on coding with thoughtful system design and a culture of continuous improvement to deliver resilient, highly scalable technology that keeps our Commodities and Global Markets business ahead of the curve. Leveraging best-in-class open-source frameworks and cloud-native services, you’ll design, build and run the distributed-compute and data-science platform that powers Macquarie’s trading and analytics workflows. Working side-by-side with quantitative analysts and trading desks worldwide, you’ll transform research concepts into production-ready solutions—automating infrastructure with Python, Java or Scala and embedding AI-driven capabilities that boost developer productivity and unlock new insights.

Requirements

• Advanced software engineering expertise in Python, Java or Scala, with experience designing, building and supporting production-grade distributed compute and data science platforms.
• Strong cloud engineering capability, including AWS, Kubernetes and Infrastructure-as-Code tools such as Terraform, CloudFormation and Helm.
• Experience with modern engineering practices including CI/CD pipelines, Bazel, Git-based workflows, Linux administration and networking.
• Knowledge of analytics and AI technologies, including Apache Airflow, Dask, JupyterHub, LLMs, agentic AI frameworks, MCP tools and prompt engineering.
• Excellent communication and stakeholder management skills, with a collaborative, inquisitive and agile approach to partnering with quantitative analysts, traders and other business stakeholders.

Benefits

• 1 wellbeing leave day per year and a minimum of 25 days of annual leave.
• 20 weeks’ paid parental leave for primary caregivers along with 12 days of paid transition leave upon return to work and 6 weeks’ paid leave for secondary caregivers.
• 2 days of paid volunteer leave and donation matching.