Data Engineer – Fulfillment Optimization

About the role

Join Amazon's Supply Chain Optimization Technologies (SCOT) as a Data Engineer supporting the Fulfillment Optimization team. You will help build and maintain the data foundations that power AI‑driven planning and execution systems used to ship billions of items worldwide.

Key responsibilities

• Design, build, and optimize physical data models and ETL pipelines on Amazon platforms such as Redshift, EMR, Spark, S3, and Hive.
• Translate well‑defined requirements from Data Scientists, BI Engineers, and Software Engineers into tested, documented, and maintainable data solutions.
• Troubleshoot, root‑cause, and improve existing datasets and pipelines, enhancing reliability and maintainability.
• Measure and improve dataset quality (completeness, freshness, correctness) and contribute to monitoring and SLA frameworks.
• Write secure, stable, testable, and well‑documented code in SQL and Python (or Scala) and participate in code reviews.
• Classify, store, and handle data in compliance with Amazon’s security and privacy policies.
• Collaborate with cross‑functional teams to integrate data sources and unblock dependencies.

Required profile

• Passion for working with large‑scale, complex data sets.
• Attention to detail and commitment to delivering high‑quality solutions on schedule.
• Willingness to learn the team’s data architecture deeply and evolve it over time.
• Ability to work collaboratively with applied scientists, engineers, and business stakeholders.

Required skills

• SQL
• Python (or Scala)
• Amazon Redshift
• Amazon EMR
• Apache Spark
• Amazon S3
• Hive