Business Intelligence Engineer, Marketing and Prime

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.

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

Acknowledgement of country:
In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.

IDE statement:
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.