S&OP Supply Chain Manager - Data-Driven Planning

Amazon; Tempe (AZ); On-site; USD 115,000 - 160,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

RSUs

Job summary

Amazon is seeking a Supply Chain Manager in Sales and Operations Planning (S&OP) to own high‑level planning for the fulfillment network in Tempe, AZ. You will balance demand and supply with data-driven decisions while collaborating across multiple groups, from warehouse teams to senior leaders.

You will lead cross-functional efforts to optimize inventory, transportation costs, and labor capacity, and shape the long-term network strategy in a fast-paced environment where quick, data-informed

Qualifications

• 5+ years of program or project management experience.
• 5+ years of supply chain experience.
• Experience using data and metrics to determine and drive improvements.
• Experience owning program strategy, end to end delivery, and communicating results to senior leadership.

Responsibilities

• Successfully operate and influence in a cross-functional capacity to create the 16 week S&OP plan.
• Data mine by leveraging SQL to influence key business decisions.
• Demonstrate strong Customer focus.
• Work with tech teams to streamline the planning tools for accuracy and efficiency.
• Identify, prioritize, and implement processes to eliminate defects in the supply chain.
• Create, develop, and drive solutions that lead to a richer end to end customer experience.
• Execute thorough root cause analysis and deliver results.

Skills

Program management

Supply chain

Data analysis

Stakeholder management

Leadership

Education

MBA or Master's degree

Tools

SQL

Job description

Amazon is seeking a Supply Chain Manager in Sales and Operations Planning (S&OP) to own high‑level planning for the fulfillment network in Tempe, AZ. You will balance demand and supply with data-driven decisions while collaborating across multiple groups, from warehouse teams to senior leaders.

You will lead cross-functional efforts to optimize inventory, transportation costs, and labor capacity, and shape the long-term network strategy in a fast-paced environment where quick, data-informed