Amazon strives to exceed the expectations of our customers by ensuring shipments are delivered quickly, safely, and as compliant as possible.
Amazon is looking for a Business Intelligence Engineer Risk Intelligence to support the vision of TRC.
Amazon’s Transportation Risk and Compliance Team (TRC) protects Amazon’s various transportation businesses by implementing scalable risk management solutions that foster continued business growth.
To support the business, we build intelligent and insightful reporting such that transportation business and auditing teams can make informed decisions and maintain a healthy gearing ratio.
To help fulfill this mission, the analytics and reporting team aims to influence auditing and business decisions by delivering sophisticated risk monitoring models, analytical tools and frameworks.
As a Business Intelligence Engineer (BIE) on the team, you will work closely with our business and auditing stakeholders, as well as the other members of our team, to provide recommendations and insights through your in-depth analyses and reporting.
We are open to hiring candidates to work out of one of the following locations :
Arlington, VA Seattle, WA Nashville, TN
BASIC QUALIFICATIONS
- 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 writing complex SQL queries
- 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
PREFERRED QUALIFICATIONS
- 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
Key job responsibilities
- Collaborate with Risk Managers, Data Engineers, Software Engineers, Data Scientists, and Auditors to translate results into insights.
- Use data driven decision making to provide business recommendations for TRC / ORC leadership.
- Work autonomously and as a team to define, scope, and develop new BI solutions that can uncover issues and provide recommendations for our stakeholders.
- Improve the scalability and timeliness of existing models and visualizations by ensuring that they empower decision making and opportunities for deep dive analyses.
- Define new metrics and / or refine existing metrics in a way that helps quantify risk and presents a dynamic risk profile of the organization.
- Identify additional data sources, both internal and external, and enable their ingestion into models and frameworks.
A day in the life
Are you a self-driven engineer who enjoys coming up with creative new solutions. Continue your journey with us as a BIE! Participate in strategic planning sessions, shaping the path to data-driven success.
Dive deep into challenging customer problems, creating powerful dashboards and workflows that transform raw data into actionable intelligence.
Uncover new data streams, fueling your curiosity and innovation. Engage in deep-dive analysis, unlocking the narratives hidden within the numbers.
Elevate your impact by presenting ground breaking ideas to leaders. This role invites you to be the architect of intelligence, sculpting the future of business insights for TRC.
Join us and unleash your potential!
BASIC QUALIFICATIONS
- 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
PREFERRED QUALIFICATIONS
- 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
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