Amazon.com Services LLC

Data Science, Data Engineering, transportation and logistics

DataEngineerII,UTRDataEngineering

$132–179k Bellevue, Washington, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Data Engineer II, UTR Data Engineering at Amazon.com Services LLC. Skills: Data engineering, AI-native approach, Data architecture, Data models. Design logical and physical data models. Create coherent models”

What You'll Achieve.

Deliver data solutions impacting planning accuracy

Industry & Context.

Data Science, Data Engineering, transportation and logistics
Problems you'll solve

Root cause analysis

What They're Looking For.

Must Have

3+ years data engineering experience, 1+ years developing/operating large-scale data structures for BI analytics using ETL/ELT, 1+ years developing/operating large-scale data structures for BI analytics using OLAP, 1+ years developing/operating large-scale data structures for BI analytics using data modeling, 1+ years developing/operating large-scale data structures for BI analytics using SQL, 1+ years developing/operating large-scale data structures for BI analytics using Oracle, Experience with data modeling, Experience with data warehousing, Experience building ETL pipelines

Nice to Have

Experience with AWS technologies, Experience with non-relational databases

What You'll Do.

Design logical and physical data models

Create coherent models

Build and optimize ETL pipelines

Design and build configuration-driven data frameworks

Build AI agent tooling

Build MCP-based interfaces

Own ongoing data quality

Implement standardized data contracts

Establish data certification processes

Automate manual quality processes

Work with planning scientists

Work with software engineers

Work with BI engineers

Work with product managers

Improve self-service access to data

Build analytical data models

Build tooling for data access

Improve engineering processes

Automate manual operations

Establish monitoring and alerting standards

Drive code quality practices

Drive dependency management practices

Train new team members

Participate in interview process

Help recruit for team

How You'll Work.

Team & Collaboration

Cross-functional teams; Planning scientists; Software engineers; BI engineers; Product managers

Full Job 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. 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. 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. If you want to learn fast and have a hand in shaping the way a team works, this is that opportunity. We are hiring a Data Engineer to own significant portions of our data architecture, drive the design of AI-powered frameworks, and deliver data solutions that directly impact planning accuracy across Amazon's delivery network. Key job responsibilities 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. 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 en

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