Amazon Development Centre Canada ULC
Business Intelligence, Business Intel Engineer, operations
BusinessIntelligenceEngineerII,FulfillmentOptimization
Neural analysis suggests this role is
optimal for Mid candidates.
“Business Intelligence Engineer II, Fulfillment Optimization at Amazon Development Centre Canada ULC. Skills: Business Intelligence, Data Engineering, Data Analysis. Retrieve data. Integrate data”
What You'll Achieve.
Improve CX; Holistic measurement of productivity; Holistic measurement of business impact; Influence decision making
Industry & Context.
Dive into complex business problems; Provide data-driven insights; Make recommendations; Identify key patterns; Quantify opportunities; Prioritize features; Find timely answers; Identify root causes; Generate business insights
What They're Looking For.
Must Have
5+ years analyzing data, Experience with Redshift, Experience with Oracle, Experience with NoSQL, Experience with Tableau, Experience with Quicksight, Experience with data modeling, Experience with data warehousing, Experience building ETL pipelines, Experience with R, Experience with SAS, Experience with Matlab, Experience using SQL, Scripting experience with Python
Nice to Have
Experience with EC2, Experience with DynamoDB, Experience with S3, Experience with Redshift, Experience in data mining, Experience with ETL, Experience using databases
What You'll Do.
Present data in dashboards
Analyze historical data
Support decision making
Present recommendations
Categorize data errors
Improve business processes
Design data architecture
Implement data architecture
Design analytics system
Implement analytics system
Standardize data management
Establish standardized metrics
Measure business impact
Develop visualizations
Measure impact of feature launches
Present progress towards OLT goals
Partner with internal stakeholders
Deliver complete solutions
How You'll Work.
Team & Collaboration
Work with software engineers; Work with product management; Work with design; Work with operations; Work with business stakeholders; Collaborate with data engineers; Collaborate with software development engineers; Collaborate with other BI engineers; Partner with internal stakeholders
Communication Scope
Verbal presentation; Written presentation
Full Job Description
Have you ever ordered a product on Amazon and wondered how it got to you so fast? Did you ever think about where this package came from and how much it cost to deliver? Join us in establishing the strategic vision and leading the transformation of Amazon's transportation network as we build real-time, intelligent, and fully automated systems that optimize package delivery across the world's most complex logistics network. We’re looking for a talented and motivated Business Intelligence Engineer who enjoys the challenge of diving into complex business problems, providing data-driven insights, and making recommendations that directly impact the business. You will work closely with software engineers, product management, design, operations, and business stakeholders to drive decisions and bring products to production across the different Amazon transportation teams. You will enable the creation of data models that will drive regional parity, scalability, programmability of every aspect of transportation systems. Your responsibility is to expose and measure the current performance of our systems, identify key patterns of success and failure, find and quantify opportunities for improvement, enable prioritization of features and faster adoption of products. Successful team members are customer obsessed, flexible, and collaborative team players who enjoy working across functions and organizations to solve problems and get results. They thrive in ambiguity, ask hard questions, and build scalable solutions that provide critical business insights necessary to influence decision making across organizations. They find timely answers buried in large data sets and complex systems, identify root causes, and are obsessed with generating business insights. Key job responsibilities - Retrieve, integrate, visualize and present data in dashboards (using Tableau, Quick sight, etc.) to support business decision making - Analysis of historical data to identify trends and support decision
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