Posted 23 July, 2026
Business Intelligence Engineer, Marketing and Prime
Amazon
AU, NSW, Sydney
Full Time
Reference: 71_654242_5469b732-4ecb-471e-be48-f748809143a4
Join Amazon's Prime and Marketing team as a Business Intelligence Engineer (BIE) to revolutionise how we understand, measure and serve our customer base. You'll architect and build enterprise-level data analytics solutions, including scalable ETL pipelines, automated AI powered reporting systems, and self-service analytics platforms that process petabytes of data daily across multiple dimensions. Working with technologies like AWS, Apache Kafka, Spark, and modern AI/ML tools, you'll create data analysis products that power critical decision-making across Amazon.
As a BIE, you'll be instrumental in defining and implementing key business metrics, building efficient dimensional data models, and leveraging advanced AI technologies like QuickSuite and ML-powered analytics. You'll design intuitive self-service platforms that enable business users to independently explore data, discover insights, and create automated reports. Beyond technical implementation, you'll lead end-to-end project execution, manage Marketing services data infrastructure, and establish key relationships across Amazon's business units. This role offers the opportunity to provide technical mentorship, drive architectural decisions, and shape the future of Amazon Marketing and Prime's data ecosystem, impacting millions of customers.
Key job responsibilities
- Architect Local Foundations: Design and develop end-to-end analytics solutions (ETL, data modelling, and warehousing) tailored to the unique challenges of the Australian marketing and prime teams.
- Drive Automation: Create automated reporting and interactive QuickSight dashboards that replace manual processes and allow stakeholders to deep-dive into performance metrics like customer engagement, marketing attribution, traffic, actuals vs. plan, etc.
- Enable Scalability: Partner with data engineers, marketing & prime teams to build the data pipelines required for predictive models, directly impacting how we measure performance. Leverage Agentic workflows to build custom models for lifecycle, performance and marketing teams.
- Process Innovation: Identify improvement opportunities at scale in our current workflows across measurement, reporting and execution systems.
- Influence Strategy: Spot trends across marketing, lifecycle and performance accuracies, goals and measurement planning, providing data-driven evidence needed to influence decisions.
As a BIE, you'll be instrumental in defining and implementing key business metrics, building efficient dimensional data models, and leveraging advanced AI technologies like QuickSuite and ML-powered analytics. You'll design intuitive self-service platforms that enable business users to independently explore data, discover insights, and create automated reports. Beyond technical implementation, you'll lead end-to-end project execution, manage Marketing services data infrastructure, and establish key relationships across Amazon's business units. This role offers the opportunity to provide technical mentorship, drive architectural decisions, and shape the future of Amazon Marketing and Prime's data ecosystem, impacting millions of customers.
Key job responsibilities
- Architect Local Foundations: Design and develop end-to-end analytics solutions (ETL, data modelling, and warehousing) tailored to the unique challenges of the Australian marketing and prime teams.
- Drive Automation: Create automated reporting and interactive QuickSight dashboards that replace manual processes and allow stakeholders to deep-dive into performance metrics like customer engagement, marketing attribution, traffic, actuals vs. plan, etc.
- Enable Scalability: Partner with data engineers, marketing & prime teams to build the data pipelines required for predictive models, directly impacting how we measure performance. Leverage Agentic workflows to build custom models for lifecycle, performance and marketing teams.
- Process Innovation: Identify improvement opportunities at scale in our current workflows across measurement, reporting and execution systems.
- Influence Strategy: Spot trends across marketing, lifecycle and performance accuracies, goals and measurement planning, providing data-driven evidence needed to influence decisions.
