Data Engineer II , UTR Data Engineering

Job summary

DESCRIPTION UTR Planning Tech builds the data infrastructure that powers labor planning across 12 Amazon last-mile and sort-center business lines. Our pipelines feed the planning systems that determine how Amazon staffs its delivery network, serving hundreds of sites and processing millions of data points daily. Our team is shifting from hand-coded, custom pipelines to an AI-native approach.

Benefits

Qualifications

• with technical
• Help shape what we build, not just how.
• Improve self-service access to data.
• Build analytical data models and tooling that reduce dependency on the DE team for common data access patterns.
• Improve engineering processes: automate manual operations, establish monitoring and alerting standards, and drive code quality and dependency management practices.
• Mentor engineers and interns.
• Train new team members on how team data solutions are constructed, how they operate, and how they fit into the broader architecture.
• Participate in the interview process and help recruit for the team.
• 3+ years of data engineering experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP
• Experience with AWS

Responsibilities

• We are early in this transformation, which means you will not inherit a finished system.
• You will help define how we build, what patterns we standardize, and how AI fits into data engineering workflows.
• UTR Planning Tech builds the data infrastructure that powers labor planning across 12 Amazon last-mile and sort-center business lines.
• Our pipelines feed the planning systems that determine how Amazon staffs its delivery network, serving hundreds of sites and processing millions of data points daily.
• Our team is shifting from hand-coded, custom pipelines to an AI-native approach.
• We are building reusable frameworks where engineers and business users define what they need through configurations and natural language instead of writing custom code for every use case.
• AI agents handle orchestration, validation, and deployment.
• If you want to learn fast and have a hand in shaping the way a team works, this is that opportunity.
• Key job
• Design and own logical and physical data models for major datasets in the team's architecture.

Skills

Industry