Business Intelligence Engineer

Job summary
Business Intelligence Engineer - LogisticsAnalyzing and interpreting dataDriving effective performance measurement and management
Job seniority: mid-to-senior level
Responsibilities
• Partner with internal stakeholders across multiple teams, gathering requirements and delivering complete solutions• Partner with Data Engineering and Software Development Engineers to prioritize and define AMZL data and BI development needs• Work with in-house scientists, global supply chain, transportation and logistics teams to identify new BI capabilities and projects• Conduct deep dive investigations into operations execution and business problems, identify opportunities, and lead or support implementation (role varies by opportunity).• Analyze and visualize large scale geo-spatial logistics and transaction data to determine user behavior or delivery process problems, and output solid analysis report with recommendation.• Serve as liaison between the WW Planning and Analytics team and the operations business teams to achieve the goal of providing actionable insights into current delivery performance, and ad hoc investigations into future improvements or innovations. This will require data gathering and manipulation, synthesis and modeling, problem solving, and communication of insights and recommendations.• Develop queries and visualizations for ad-hoc requests and projects, as well as ongoing reporting.
Requirements
• Experience with 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 writing complex SQL queries• 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• 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
Key Skills Needed
• Analyzing and interpreting data• Data visualization• Data modeling• SQL querying• Statistical analysis• Scripting (Python)• AWS solutions• Data mining