The Amazon Privacy team is on a mission to make it easy for Amazon teams to meet customer expectations and regulatory obligations when it comes to taking care of their personal data.

As a Business Intelligence Engineer for Amazon Privacy, you will own, source and deliver the metrics which enable Amazon Privacy to validate to ourselves, to our internal partners, and to our external stakeholders that we are meeting our privacy obligations across the company. To extract data and meaningful insights, you will partner with our product and engineering teams who own tools used by builders and privacy specialists across the company. You will work with product and engineering leads to discover new ways to view and report on privacy impacting initiatives.

Privacy is a fascinating, fast-moving and ever-changing area - there's still many opportunities for invention and innovation ahead of us.

Key job responsibilities
You will own sourcing data to be used in our internal dashboards, as well as our regular business reviews, weekly, monthly, and quarterly. You will work with the Amazon Privacy product team to build a scalable ongoing metrics and analytics program. You will research the impact of privacy automation and tooling on both customers and business users. You will coordinate with our internal auditing team to ensure we have the data necessary as part of our overall evidence of compliance program.

About the team
We own software products that teams use to identify their privacy obligations, as well as the products they use to support those obligations in their software.

We partner with core builder framework teams, privacy legal, and privacy specialists across the company. Our teams are in Arlington VA, Austin TX, Seattle WA and Romania.

Privacy knowledge is beneficial but not at essential. Many of us learned on the job, having come from other Amazon teams.

- 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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