Business Intelligence Engineer, Decision Science and Technology (AST)

- 5+ 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 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
- Experience in Statistical Analysis packages such as R, SAS and Matlab

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Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $89,600/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Decision Science and Technology is seeking an entrepreneurial, innovative and self-driven Business Intelligence Engineer to join our team, and develop analytics insights and reporting tools to reduce maintenance costs, increase safety and promote sustainability. This role is global in scope and will impact KPIs across multiple business programs in Reliability and Maintenance Engineering (RME).

In this role, the candidate will partner closely with product managers, program managers, business stakeholders, and scientists to build reporting data models, business KPIs to support high judgment decisions. You will go beyond report generation and invest in automation to scale the analytics needs for all business and technical stakeholders. You will be exposed to a wide range of technologies, systems, and business challenges across Energy & Sustainability, Labor planning and Spare Parts (inventory management).

The Business Intelligence Role in RME will participate in the design, implementation, and delivery of business intelligence solutions to address complex and ambiguous business challenges. In addition to it, this role will perform in-depth analyses of business problem statements and provide conclusions and recommendations to leadership. The role requires one to identify opportunities to enhance analytical reporting and streamline and automate reporting, audits, and other data-driven tasks. This role also will work on data engineering aspects to improve data infrastructure, ensure data availability, and expand access to customer insights.


A day in the life
A typical day in this role may involve:

1) Developing innovative solutions using advanced data analytics tools

2) Work collaboratively with Product/Program Mgrs., Business Stakeholders and Scientists.

3) Exhibit outstanding verbal and written communication abilities

4) Identify and prioritize high-impact projects that drive business growth

5) Demonstrate skill in influencing business owners and supporting strategic decision-making processes

The position requires an individual who can effectively guide leaders, contribute to thoughtful decision-making, and thrive in a rapidly evolving landscape. The role offers opportunities to create data-driven solutions, pinpoint high-priority work, and address intricate problems that shape the RME's strategic direction



About the team
The mission of our team is to leverage the use of data, science and technology to improve the efficiency of RME maintenance activities, reduce costs, increase safety and promote sustainability while creating frictionless customer experiences. We work across different research areas such as Computer Vision, Inventory management, Anomaly detection, Optimization and Natural Language processing (NLP).