Business Intelligence Engineer 1, Amazon Pay India

Job ID: 2896281 | Amazon Pay (India) Private Limited

Amazon's vision is to be the earth's most customer-centric company. The ambition of the Amazon payments business is to transform payments in India. The payments data team provides data and insights to the partner verticals to enable them to make informed decisions. This role requires teamwork and a business perspective. The individual will interact extensively with team members across business lines, working in partnership with Pay Finance, Data Engineering, and Central Customer Analytics teams. There will be a steep learning curve, adding significant business skills to the individual.

Key Job Responsibilities

  1. Ability to do exploratory analysis: Fetch data from systems and analyze trends.
  2. Identify consumer segments that need to be actioned to drive adoption of Amazon Pay.
  3. Develop India-specific customer segmentation models to improve the efficiency of marketing and financing product roadmap inputs.
  4. Establish mechanisms for cross-functional teams to consume customer insights to improve engagement along the customer life cycle.
  5. Work with cross-functional teams.

About the Team

The ambition of the Amazon payments business is to transform payments in India. The payments data team provides data and insights to the partner verticals to enable them to make informed decisions.

BASIC QUALIFICATIONS

  • 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL, etc.
  • 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.

PREFERRED QUALIFICATIONS

  • 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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