Business Intelligence Engineer, Search Data Science

- 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
- 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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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.
Amazon is one of the most popular sites in the US. Our product search engine, one of the most heavily used services in the world, indexes billions of products and serves hundreds of millions of customers world-wide. Our team leads the data science and analytics efforts for the search page and we own multiple aspects of understanding how we can measure customer satisfaction with our experiences. This includes building science based insights and novel metrics to define and track customer focused aspects. We manipulate massive amounts of data, terabytes worth a day, coming from multiple different systems with a high degree of complexity in structure, schema and different levels of quality. We are looking for a Business Intelligence Engineer to build metrics, deep dive and generate insights to improve the customer experience with a high level of senior leadership visibility. These metrics govern the quality of the search page and impact multiple organizations and teams that contribute to the search results and ultimately what customers use to make purchase decisions on the website.

Key job responsibilities
You will be building and improving metrics that measure the quality of the search page. This includes working backwards from customer pain points, managing large and complex data pipelines manipulating terabytes of data a day. Your metrics and dashboards will be used by multiple teams and senior leaders and you will be providing insights into opportunities to improve the customer experience and our signals and systems. The metrics and underlying pipelines are used daily for decision making, setting up experiments, defining goals and influencing senior leaders to set priorities.

About the team
The mission of the Search Data Science team is to build a world class shopping experience that delights customers. We focus on the long term and big picture, ensuring that the search page is balancing strategic trade-offs. We bring to this effort expertise in constrained optimization, causal inference, and marketplace equilibrium effects. We build systems, metrics, and mechanisms to ensure that product decisions are scientifically sound. We develop models to estimate the downstream dollar value of the quality of the experience. We spend time on evaluating experiments to develop durable learnings.