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Business Intel Engineer I, Global Operations - Artificial Intelligence: Amazon

Aug 31, 2025   |   Location: Hyderabad, Telangana, India   |   Deadline: Not specified

Experience: Mid

Continent: Asia

The Global Operations – Artificial Intelligence (GO-AI) team is an initiative that remotely handles exceptions in Amazon's Robotic Fulfillment Centers worldwide. The team complements automated, vision-based technologies by providing remote human support for tasks requiring higher cognitive ability. GO-AI provides end-to-end solutions and operates multiple programs in partnership with global technology and operations teams.

Responsibilities:

Maintain and refine ETL (Extract, Transform, Load) processes and write secure, stable, and maintainable code to automate manual tasks.

Use industry analytics visualization tools (e.g., Excel, Tableau, QuickSight, PowerBI) and statistical methods to deliver actionable insights.

Build and own small to mid-size Business Intelligence (BI) solutions, including reports, dashboards, and analyses, to answer business questions.

Understand data lineage, including data sources, metric aggregation, and how the resulting intelligence is consumed and acted upon.

Partner with peer Business Intelligence Engineers (BIEs) to troubleshoot, research root causes, and propose solutions.

Requirements:

Basic Qualifications:

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

Experience building and maintaining basic data artifacts (e.g., ETL, data models, queries).

Experience with one or more industry analytics visualization tools (e.g., Excel, Tableau, QuickSight, PowerBI) and statistical methods.

Experience with a scripting language (e.g., Python, Java, or R).

Experience applying basic statistical methods (e.g., regression) to business problems.

Preferred Qualifications:

A Master's degree or an advanced technical degree.

Experience with statistical analysis and correlation analysis.

Knowledge of how to improve code quality and optimize BI processes (e.g., for speed, cost, reliability).

Excellence in technical communication with peers, partners, and non-technical cohorts.
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