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 data engineer to build and maintain large and complex data pipelines, orchestrated for daily updates with a very high level of senior leadership visibility. These pipelines bring together data from multiple sources with complex structure. You will be creative with ETL techniques to optimize these jobs for performance and cost.

Key job responsibilities

You will be managing large and complex data pipeline 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.

BASIC QUALIFICATIONS

- 10+ years of professional or military experience

- 5+ years of SQL experience

- Experience programming to extract, transform and clean large (multi-TB) data sets

- Experience with theory and practice of design of experiments and statistical analysis of results

- Experience with AWS technologies

- Experience in scripting for automation (e.g. Python) and advanced SQL skills.

- Experience with theory and practice of information retrieval, data science, machine learning and data mining

PREFERRED QUALIFICATIONS

- Experience working directly with business stakeholders to translate between data and business needs

- Experience managing, analyzing and communicating results to senior leadership

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $117,300/year in our lowest geographic market up to $202,800/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.

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