Amazon
Business Intelligence, Business Intel Engineer, international stores
BusinessIntelligenceEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Business Intelligence Engineer at Amazon. Skills: Business Intelligence, Data Engineering, Statistical Analysis. Partner with engineering, product, business and finance teams. Create key performance indicators”
What You'll Achieve.
Drive strategic business decisions; Drive incremental signups or revenue
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
5+ years analyzing data, 5+ years Redshift experience, 5+ years Oracle experience, 5+ years NoSQL experience, Experience data visualization, Experience data modeling, Experience building ETL pipelines, Experience Statistical Analysis packages, Experience using SQL, Scripting experience Python
Nice to Have
Experience AWS solutions, Experience data mining, Experience ETL, Experience using databases large-scale complex datasets
What You'll Do.
Partner with engineering
business and finance teams
Create key performance indicators
Create new methodologies for measurement
Translate data into actionable insights
Create analytical insights
Identify key priorities
Make and justify recommendations
Determine best-in-class performance reports
Automate reporting for regular metrics
Identify areas of opportunity to automate
Scale ad hoc analyses
Build and inform BI tool improvements
Provide requirements for telemetry
Provide requirements for data structure
Drive strategic business decisions
Drive incremental signups or revenue
Define business critical metrics
Develop business critical metrics
Define reports across international business levers
Develop reports across international business levers
Define key performance indicators
Develop key performance indicators
Own alignment of analytical initiatives
Own standardization of analytical initiatives
Drive efforts across international business leaders
Drive efforts across BI leaders
Drive efforts across executive management
Own key executive reports
Own metrics consumed by VPs and Directors
Provide thought leadership in global business deep dives
How You'll Work.
Team & Collaboration
Engineering teams; Product teams; Business teams; Finance teams; Global leaders; Global teams; International business leaders; BI leaders; Executive management
Communication Scope
Analytical communication
Full Job Description
Amazon’s Consumer Payments organization is seeking a highly quantitative, experienced Business Intelligence Engineer to drive the development of analytics and insights. You will succeed in this role if you are an organized self-starter who can learn new technologies quickly and excel in a fast-paced environment. In this position, you will be a key contributor and sparring partner, developing analytics and insights that global executive management teams and business leaders will use to define global strategies and deep dive businesses. Our team offers a unique opportunity to build a new set of analytical experiences from the ground up. You will be part the team that is focused on acquiring new merchants from around the world to payments around the world. The position is based in India but will interact with global leaders and teams in Europe, Japan, US, and other regions. You should be highly analytical, resourceful, customer focused, team oriented, and have an ability to work independently under time constraints to meet deadlines. You will be comfortable thinking big and diving deep. A proven track record in taking on end-to-end ownership and successfully delivering results in a fast-paced, dynamic business environment is strongly preferred. Key job responsibilities - Partnering with engineering, product, business and finance teams to create key performance indicators and new methodologies for measurement - Fluency in analytical communication to translate data into actionable insights for stakeholders both in and out of the team, create analytical insights to identify key priorities - Proactively make and justify recommendations based on advanced statistical techniques, deep familiarity with the customer or developer experiences, as well as by cross-referencing multiple data sources and comparing against the wider industry - Determine best-in-class performance reports and automate reporting for regular metrics, identify areas of opportunity to automate, scale ad-hoc
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