Business Intelligence Engineer, ROW Supply Chain Analytics, Research and Product

- 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 with forecasting and statistical analysis
- 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 developing and presenting recommendations of new metrics allowing better understanding of the performance of the business

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Amazon’s ROW (Rest of World) Supply Chain Analytics team is looking for talented Business Intelligence Engineers who develop solutions to better manage/optimize speed and operations planning while providing the best experience to our customers at the lowest possible price. Our team members have an opportunity to be at the forefront of supply chain thought leadership by working on some of the most difficult problems with some of the best research scientists, product/program managers, software developers and business leaders in the industry, shaping our roadmap to drive real impact on Amazon's long-term profitability. We are an agile team, building new analysis from ground up, proposing new concepts and technology to meet business needs, and enjoy and excel at diving into data to analyze root causes and implement long-term solutions.
As a BIE within the group, you will analyze massive data sets, identify areas to improve, define metrics to measure and monitor programs, build models to predict and optimize and most importantly work with different stakeholders to drive improvements over time. You will also work closely with internal business teams to extract or mine information from our existing systems to create new analysis, build analytical products and cause impact across wider teams in intuitive ways. This position provides opportunities to influence high visibility/high impact areas in the organization. They are right a lot, work very efficiently, and routinely deliver results on time. They have a global view of the analytical and/or science solutions that they build and consistently think in terms of automating, expanding, and scaling the results broadly. This position also requires you to work across a variety of teams, including transportation, operations, finance, delivery experience, people experience and platform (software) teams. Successful candidates must thrive in fast-paced environments which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, extract and manipulate data across various data marts, and align research focuses on Amazon’s strategic needs.
We are looking for people with a flair for recognizing trends and patterns while correlating it to the business problem at hand. If you have an uncanny ability to decipher the exact policy/mechanism/solution to address the challenge and ability to influence folks using hard data (and some tact) then we are looking for you!

Key job responsibilities
• Analysis of historical data to identify trends and support decision making, including written and verbal presentation of results and recommendations
• Collaborating with product and software development teams to implement analytics systems and data structures to support large-scale data analysis and delivery of analytical and machine learning models
• Mining and manipulating data from database tables, simulation results, and log files
• Identifying data needs and driving data quality improvement projects
• Understanding the broad range of Amazon’s data resources, which to use, how, and when
• Thought leadership on data mining and analysis
• Modeling complex/abstract problems and discovering insights and developing solutions/products using statistics, data mining, science/machine-learning and visualization techniques
• Helping to automate processes by developing deep-dive tools, metrics, and dashboards to communicate insights to the business teams
• Collaborating effectively with internal end-users, cross-functional software development teams, and technical support/sustaining engineering teams to solve problems and implement new solutions