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Business Intelligence Engineer, Alexa Audio Data and Insights

Amazon is a global leader in e-commerce and cloud computing, known for innovation in technology and customer service.
$89,600 - $185,000
Data
Senior Software Engineer
5,000+ Employees
3+ years of experience
AI · Enterprise SaaS
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Description For Business Intelligence Engineer, Alexa Audio Data and Insights

Want to transform the way people enjoy music, podcasts, radio, and audiobooks? Then come join the team that delivers the global audio experience on Alexa. If you're passionate about building magical experiences for customers, while solving hard, complex technical problems, then this role is for you. Work with us to deliver industry leading experiences across a growing array of Alexa supported devices and countries, all while being at the forefront of Generative AI and LLM capabilities.

The Alexa Audio org is seeking an experienced Business Intelligence Engineer who is a master of both data insights and relationship-building. Using a special combination of technical and people skills, this candidate will be the key BI liaison between Alexa audio feature owners and other partner teams. Primary areas of focus will be 1) audio feature launch support 2) defining metrics and KPIs, and deep-diving ambiguous and large data sets.

A successful candidate will be an expert with SQL, ETL (and general data wrangling) and have exemplary communication skills. The candidate will need to be a self-starter, comfortable with ambiguity in a fast-paced and ever-changing environment, and able to think big while paying careful attention to detail.

Key job responsibilities:

  • Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions
  • Interface with business customers, gathering requirements and delivering complete reporting solution
  • Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
  • Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
  • Perform creative deep dive analyses to explain findings
  • Interact with internal stakeholders to share insights from monitoring and deep dive analyses
  • Drive instrumentation as part of organization-wide programs and enhancements

The team consists of 12 members, including Business Intelligence Engineers, Data Engineers, and Data Scientists, who bring deep experience in both business analytics and data science. They cover the data needs of Music, Radio, Podcast, Books, and the Audio Category, working closely with Alexa Audio Product Managers, Engineering, Finance, Alexa analytics and science teams, Alexa International, and the Alexa Analytics and Science Community.

Last updated 8 months ago

Responsibilities For Business Intelligence Engineer, Alexa Audio Data and Insights

  • Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions
  • Interface with business customers, gathering requirements and delivering complete reporting solution
  • Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
  • Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
  • Perform creative deep dive analyses to explain findings
  • Interact with internal stakeholders to share insights from monitoring and deep dive analyses
  • Drive instrumentation as part of organization-wide programs and enhancements

Requirements For Business Intelligence Engineer, Alexa Audio Data and Insights

Python
  • 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

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