Senior BI Engineer, Personalization

- * Bachelor’s degree in engineering, statistics, computer science, mathematics or equivalent quantitative field
- * 7+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- * Experience in Business Intelligence, Data Analysis, or a similar role.
- * Ability to operate independently and deal with ambiguity in a fast-paced environment.
- * Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
- * Experience with building ETL pipelines
- * Experience with data visualization using Tableau, Quicksight, or similar tools
- * Exceptional communication skills (verbal & written), with the ability to convey complex ideas in a clear and concise manner.
- * Strong problem-solving skills.
- Master’s degree in finance, engineering, statistics, computer science, mathematics or equivalent quantitative field
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Strong understanding of A/B testing, sampling methodologies, and other statistical analysis
About our organization:
We are part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the most personalized shopping experiences for our customers.

About the team
Our vision is to deliver a personalized search and conversational shopping experiences for Amazon customers. We recognize that each customer is different, and strive to save customers valuable time by tailoring their search journey to their individual needs, interests, and preferences. Our goal involves identifying personalization opportunities to develop and optimize customer experiences, thereby improving the overall search and discovery process across Amazon.

In this senior leadership role, you will proactively seek to understand our business objectives and identify ways to use data to help our teams make informed business decisions. You will work closely with stakeholders from across the company to understand their business questions, translate those questions into requirements, and then build data-driven solutions to empower new understanding. You will collaborate cross-functionally with product, data engineering, software engineering and applied-science teams to answer key business questions. You will be an expert in how and why stakeholders use the data produced by our team. You will dive deep into existing and new data sources, creating unique and actionable insights that improve our understanding and trends, while also identifying new opportunities to improve how our customers interact with our CXs.

You will be hands-on in data analysis and and an expert in A/B testing, using your insights to inform decisions and provide high quality communication to senior leadership.

Key job responsibilities
* Work with our internal and external partners translating business questions into an analytical framework that can be answered with existing data using BI tools and producing the required data if it is not immediately available.
* Demonstrating curiosity about business questions and an ability to reason with data, leveraging your knowledge of the wider product and business landscape to explain trends in data and the relationships between different data elements, and to suggest, prioritize, and explore paths for further analysis.
* Build efficient, scalable data solutions (ETLs, queries, reports, dashboards and analyses) that accurately address the business questions at hand.
* Produce meaningful, timely, and actionable deep dives to inform Personalization business decisions.
* Ensuring data and code quality through all stages of data acquisition, processing, and delivery.
* Collaborate effectively with colleagues who are experts in a range of disciplines, including business, science, and engineering.
* Lead projects or components from start to finish including project management, data gathering and manipulation, synthesis and modeling, problem solving, and communication of insights and recommendations.