Senior Data Product Manager, Supply Chain Analytics

Socket.dev; Pittsburgh (Allegheny County); Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

Generous employee discount

Summer Fridays

Casual dress code

Hybrid schedule

FOMO events

Job summary

American Eagle is seeking a Sr. Data Product Manager in Pittsburgh, PA or New York, NY. You will own end-to-end data assets for inventory optimization, logistics efficiency, and demand forecasting, turning ERP/WMS/TMS data into a single source of truth for real-time decisions.

You’ll bridge business logic with data engineering, lead data pipelines, and guide analytics products with a focus on scalable modeling and governance. Hybrid work and strong SQL/BI skills are essential.

Qualifications

• Bachelor’s degree in a quantitative field.
• 5+ years in data-focused roles, incl. 2+ years in Supply Chain, Logistics, or Retail Ops.
• Experience as Product Owner in Agile/Scrum environment.
• Strong SQL and cloud data warehouse experience (BigQuery, Databricks, Snowflake).
• Experience with BI tools (Tableau/Looker/Power BI).
• Able to translate business requirements into technical specs.

Responsibilities

• Define and execute multi-year data strategy for Supply Chain domain.
• Translate business requirements into detailed technical user stories and diagrams.
• Design scalable supply-chain data schemas for long-term use.
• Oversee ELT/ETL pipelines and analytics products with low latency dashboards.
• Collaborate with S&OP, Procurement, Logistics on AI/ML for analytics.

Skills

SQL

Data Analytics

Stakeholder Management

Agile/Scrum

Communication

Education

Bachelor's Degree in a quantitative field

Tools

BigQuery

Databricks

Snowflake

Job description

American Eagle is seeking a Sr. Data Product Manager in Pittsburgh, PA or New York, NY. You will own end-to-end data assets for inventory optimization, logistics efficiency, and demand forecasting, turning ERP/WMS/TMS data into a single source of truth for real-time decisions.

You’ll bridge business logic with data engineering, lead data pipelines, and guide analytics products with a focus on scalable modeling and governance. Hybrid work and strong SQL/BI skills are essential.