Amazon Sr Business Intelligence Engineer Specialized Sourcing Analytics Level 

United States, New York, New York 

790840674

The SCOT Forward Looking Inventory Planning (FLIP) team owns the systems and processes required to provide vendors with the advance signals they need to produce and place the right inventory at the right place at the right time. As BIE, you will be be working with product managers and engineers to design and develop new business intelligence solutions using large scale data technologies and drive better decision for Amazon and for the customers.Key job responsibilities
* Create actionable business insights through analytical and statistical rigor to answer key business questions, inform decision-making, and develop recommendations to improve operations.
* Design and develop robust data pipelines, write complex SQL queries and ETL processes to build new metrics and analyses.
* Collaborate cross-functionally with Product Managers, Software Engineers, and Data Scientists to -build critical business metrics, automated self service analytical dashboards and reporting.
* Navigate ambiguity around complex supply chain concepts to develop analytical solutions and provide mentorship to junior team members.
* Analyze relevant business data, uncover trends and correlations, and translate insights into clear recommendations to improve inventory planning and forecasting.
* Drive operational excellence by applying strategic thinking, making informed trade-off decisions, and aligning both business and engineering priorities.
* Maintain ETL and business metric and health of data pipelines

- 6+ years of SQL experience
- 6+ years of professional or military experience
- Experience programming to extract, transform and clean large (multi-TB) data sets
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.
- Experience with AWS technologies
- Experience with theory and practice of design of experiments and statistical analysis of results
- Experience with theory and practice of information retrieval, data science, machine learning and data mining