Data Engineer II , UTR Data Engineering

Amazon is hiring a Data Engineer II , UTR Data Engineering in Bellevue, United States. It pays $132k-$179k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this data engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
The posting mentions AI agents, data engineering and data modeling among its tools and skills.
Level classes it as a mid-level role.
Amazon has 20,000+ other open roles on Level.

AI in this role

Design and implement AI-powered data pipelines and frameworks for labor planning infrastructure.

ai-agentsdata-engineeringdata-modelingnatural-language-processingpipelines

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 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

* Design and own logical and physical data models for major datasets in the team's architecture. Create coherent models that drive physical design and serve multiple downstream consumers.
* Build and optimize ETL pipelines for complex datasets using AWS services (Redshift, S3, EMR, Glue, Lambda, Athena) and Python-based orchestration (Airflow/MWAA). Your solutions will be testable, maintainable, and efficient.
* Design and build configuration-driven data frameworks that replace repetitive custom code with reusable, declarative patterns for ingestion, transformation, and metric curation. Own the design of these frameworks, not just the implementation.
* Build AI agent tooling and MCP-based interfaces that allow conversational agents to generate SQL, validate configurations, manage data quality rules, and execute pipeline operations through natural language.
* Own ongoing data quality for datasets you build. Implement standardized data contracts, define SLAs, establish data certification processes, and automate manual quality processes.
* Work with planning scientists, software engineers, BI engineers, and product managers to balance customer requirements with technical requirements. 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.

Basic qualifications

- 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 technologies experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience
- Experience with data modeling, warehousing and building ETL pipelines

Preferred qualifications

- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Bellevue - 132,100.00 - 178,800.00 USD annually

How we rate this

Data Engineer II , UTR Data Engineering at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Engineer II , UTR Data Engineering is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $132k-$179k a year.
The role is based in US, WA, Bellevue.
The job was posted on September 16, 2026.
Seniority: mid.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsData EngineeringData ModelingNatural Language ProcessingPipelines

Also common in data engineer jobs at this level

Spark Databricks Machine learning Azure Generative AI Snowflake

Pay

This job starts at: $132k
Typical data engineer job: $145k

This posting starts 9% below the typical data engineer job. See data engineer jobs

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where data modeling was part of your work. What did you do?
Tell me about a project where natural language processing was part of your work. What did you do?
Tell me about a project where pipelines was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI agents, Data Engineering, Data Modeling, Natural Language Processing, and Pipelines. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

Get your CV reviewed before you apply

Send your CV and the role you want next. Your review arrives by email within 3 days.

Get a free CV review Check your resume with the ATS resume checker