Amazon

Business Intelligence Engineer, Global Operations - AI

Posted On

May 2, 2024

Location

Virtual, Virtual

Experience Level

Freshers/Experienced

Job Type

Corporate Operations

Apply By

Oct. 1, 2024

Job Description

Want to join the Earth’s most customer centric company? Do you like to dive deep to understand problems? Are you someone who likes to challenge Status Quo? Do you strive to excel at goals assigned to you? If yes, we have opportunities for you. Global Operations - AI (GO-AI) at Amazon is looking to hire candidates who can excel in a fast-paced dynamic environment.

The Global Operations - AI (GO-AI) team is an initiative, which remotely handles exceptions in the Amazon Robotic Fulfillment Centers Globally. GO-AI seeks to complement automated vision based decision-making technologies by providing remote human support for the subset of tasks which require higher cognitive ability and cannot be processed through automated decision making with high confidence. This team provides end-to-end solutions through inbuilt competencies of Operations and strong central specialized teams to deliver programs at Amazon scale.

Are you somebody that likes to use and analyze big data to drive business decisions? Do you enjoy converting data into insights that will be used to enhance customer decisions worldwide for business leaders? Do you want to be part of the data team which measures the pulse of innovative projects? If your answer is yes, join our team. GO-AI is looking for a motivated individual with strong skills and experience in building new business intelligence solutions end-to-end. The ideal candidate will be passionate about working with big data sets and have the expertise to utilize these data sets to derive insights, answer business questions and drive growth.

Key job responsibilities
• Design, develop and maintain scaled, automated, user-friendly systems, reports, dashboards, etc. that will support our analytical and business needs for customer promise and operations.
• Use analytical and statistical rigor to solve complex problems and drive business decisions that will help us achieve our strategic goals.
• Ability to invent, refine and develop your BI solutions to ensure they are meeting the needs of the GO-AI goals
• Ability to maintain and refine straightforward ETL and create, populate data structures using one or more schema definition languages (e.g. DDL, SDL, XSD, RDF). Ability to write secure, stable, testable, maintainable code with minimal defects and automate manual processes where possible.
• Focus on operational excellence: constructively identifying quality issues, proposing solutions when necessary, taking on projects that improve your team’s BI solutions, and making them better and easier to maintain.
• Good understanding of the relevant data lineage: including sources of data; how metrics are aggregated; and how the resulting business intelligence is consumed, interpreted and acted upon by the business where the end product enables effective, data-driven business decisions.
• Having high responsibility for the code, queries, reports and analyses that are inherited or produced and having analyses and code reviewed periodically.
• Effective partnering/mentoring/developing with peer BIEs and others in your team to troubleshoot, research root causes, propose solutions, by either take ownership for their resolution or ensure a clear hand-off to the right owner. Participation in team design, scoping, and prioritization discussions.

About the team
The Global Operations - AI (GO-AI) team handles exceptions remotely in the Amazon Robotic Fulfillment Centers Globally. GO-AI seeks to complement automated vision based decision-making technologies by providing remote human support for the subset of tasks which require higher cognitive ability and cannot be processed through automated decision making with high confidence. This team provides end-to-end solutions through inbuilt competencies of Operations and strong central specialized teams to deliver programs at Amazon scale. - 5+ 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

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