Business Intelligence Engineer, Music Analytics Lead, Data Insights Specialist, DISCO M&G

hace 1 semana


Ciudad de México, Ciudad de México Amazon A tiempo completo
About the Role

We are seeking a highly skilled Business Intelligence Engineer to join our Data, Insights, Science and Optimization, Marketing & Growth (DISCO M&G) team at Amazon. As a Business Intelligence Engineer, you will play a key role in leading the analytics and insights efforts for an Amazon Music program.

Key Responsibilities
  1. Lead the development of data-driven insights and analytics solutions to inform business decisions.
  2. Collaborate with cross-functional teams to design and implement data pipelines, self-service analytics, and predictive models.
  3. Work closely with stakeholders to identify business needs and develop data visualizations and reports to support strategic goals.
  4. Develop and maintain large-scale data warehouses and data marts to support business intelligence and analytics.
  5. Design and implement data quality and governance processes to ensure data accuracy and integrity.
  6. Partner with analytics and science teams to develop and deploy machine learning models and algorithms.
  7. Educate and evangelize across internal teams on analytics, insights, and measurement best practices.
About the Team

The DISCO M&G team is a dynamic and fast-paced environment that focuses on accelerating Amazon Music customer growth by empowering Marketing & Growth teams to make sound, customer-centric decisions through data and insights. We build data pipelines, self-service analytics, insights, and predictive models enabling acquisition, engagement, and retention at scale with personalized customer touchpoints.

Requirements
  1. 3+ years of experience analyzing and interpreting data with Redshift, Oracle, NoSQL, etc.
  2. Experience with data visualization using Tableau, Quicksight, or similar tools.
  3. Experience with data modeling, warehousing, and building ETL pipelines.
  4. Experience in Statistical Analysis packages such as R, SAS, and Matlab.
  5. Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling.
Preferred Qualifications
  1. Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift.
  2. Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets.


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