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Business Intelligence Engineer II
Business Intelligence Engineer II-March 2024
Hyderabad
Mar 10, 2026
ABOUT AMAZON
Our mission is to be the world’s most customer-centric company.
10,000+ employees
Technology
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About Business Intelligence Engineer II

  Description

  Japan Transportation Systems team in Hyderabad is looking for an innovative, hands-on and customer-obsessed BIE for its Analytics function. Candidate must be detail oriented, have superior verbal and written communication skills, strong organizational skills, excellent technical skills and should be able to juggle multiple tasks at once.

  Candidate must be able to identify problems before they happen and implement solutions that detect and prevent outages. The candidate must be able to accurately prioritize projects, make sound judgments, work to improve the customer experience and get the right things done.

  This job requires you to constantly hit the ground running and have the ability to learn quickly. Primary responsibilities include defining the problem and building analytical frameworks to help the operations to streamline the process, identifying gaps in the existing process by analyzing data and liaising with relevant team(s) to plug it and analyzing data and metrics and sharing update with the internal teams.

  We are open to hiring candidates to work out of one of the following locations:

  Hyderabad, TS, IND

  Basic Qualifications

  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

  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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