Amazon's Supply Chain team is looking for a data-driven, detail-oriented Supply Chain Data Analyst to support our Inbound programs. In this role, you will own the end-to-end data lifecycle, analysis to reporting and automation & partnering with cross-functional teams to improve Vendor Experience and reduce defects.
You will work closely with Vendor Managers, In-Stock Managers, RBS, and FC Operations to identify vendor and operations pain points, build dashboards, automate workflows using AI tools, and lead weekly review cadences that drive accountability and measurable improvement.
This is a high-visibility role where your analysis directly influences operational decisions and vendor performance actions.
Key job responsibilities
Data Analysis & Reporting: Extract and analyze data to identify root causes and trends. Publish weekly reports to stakeholders.
SQL & Dashboards: Write and maintain SQL queries/ETL jobs from data warehouses. Build QuickSight/Tableau dashboards.
AI-Driven Automation: Leverage internal GenAI tools to automate flows — reducing manual effort and improving accuracy.
Weekly Review Ownership: Prepare data packs and lead the weekly calls. Track action items and ensure follow-through.
Process Improvement: Collaborate cross-functionally to establish metrics, SOPs, and process improvements that reduce upstream defect injection. Share best practices across the org.
Stakeholder Communication & Business Reviews: Translate data into actionable narratives for senior stakeholders.
Basic Qualifications
- Bachelor's degree
- 3+ years of data analysis experience
- Experience creating complex SQL queries joining multiple datasets, ETL DW concepts
- Knowledge of SQL/ETL
- Knowledge of Microsoft Excel at an advanced level, including: pivot tables, macros, index/match, vlookup, VBA, data links, etc.
- Experience with reporting and Data Visualization tools such as Quick Sight / Tableau / Power BI or other BI packages
Preferred Qualifications
- 2+ years of developing automated reporting experience
- Experience using data and metrics to drive improvements
- Knowledge of supply chain management concepts - forecasting, planning, sourcing, optimization and logistics or equivalent
- Knowledge of six Sigma/Lean processes
- Proficiency in Python for data analysis, scripting, and automation.
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