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Business Intelligence Engineer, SCOT AIM - AU
Amazon’s operations in Australia is at a unique phase of rapid expansion. As our selection and local fulfilment network grows, the complexity of managing supply chain increases. To systemically address these complexities, we are establishing a team of subject matter experts by expanding Supply Chain Optimisation Technology (SCOT) AIM team presence to Australia. We are looking for an exceptional Business Intelligence Engineer to join this specialised team and help build the analytical foundations that allow us to automate and optimize our local supply chain at scale.
- Key job responsibilities
- Architect Local Foundations: Design and develop end-to-end analytics solutions (ETL, data modeling, and warehousing) tailored to the unique challenges of the Australian supply chain.
- Drive Automation: Create automated reporting and interactive Quick Sight dashboards that replace manual processes and allow stakeholders to deep-dive into performance metrics like defect attributions, plan over plan changes, actuals over plan defects etc.
- Enable Scalability: Partner with Data Engineers & Scientists to build the data pipelines required for predictive models, directly impacting how we handle forecasting for inbounds volumes. Leverage Agentic workflows to build custom models for inbound predictions.
- Process Innovation: Identify "defects" in our current workflows across upstream planning & execution systems and manual processes that impact inbound volumes, and build scalable, AWS-native solutions to fix them.
- Influence Strategy: Spot trends across product demand forecasting accuracies, inventory efficiency and capacity planning, providing data-driven evidence needed to influence inbound volume projections or supply chain decisions on inbounds.
About the team
Have you ever ordered a product on Amazon and wondered how it got to you so fast? Wondered where it came from and how much it cost? If so, Amazon’s Supply Chain Optimization Technology (SCOT) organization is for you. At SCOT, we solve deep technical problems and build innovative solutions in a fast-paced environment. Learn more about SCOT: http://bit.ly/amazon-scot
Basic Qualifications
- 4+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
Preferred Qualifications
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience with forecasting and statistical analysis
- Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
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.
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关于Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
员工数
Seattle
总部位置
$1.5T
企业估值
评价
10条评价
3.4
10条评价
工作生活平衡
2.5
薪酬
4.2
企业文化
3.0
职业发展
3.8
管理层
2.7
65%
推荐率
优点
Great benefits and competitive pay
Learning and advancement opportunities
Good teamwork and colleagues
缺点
High pressure and long hours
Poor work-life balance
Toxic work culture and management issues
薪资范围
4个数据点
L2
L6
L3
L4
L5
L2 · Data Analyst L2
0份报告
$108,330
年薪总额
基本工资
$43,332
股票
$54,165
奖金
$10,833
$75,831
$140,829
面试评价
6条评价
难度
4.0
/ 5
时长
21-35周
体验
正面 0%
中性 17%
负面 83%
面试流程
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Technical Interview
6
Onsite/Virtual Interviews
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Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
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