Data Engineer II

As part of UTR Planning Tech within Amazon, you will help build the data infrastructure that supports labor planning across the Amazon delivery network. The work spans data architecture and engineering fundamentals, while the team moves toward an AI-native approach with reusable frameworks and conversational tooling.

This role is onsite in Bellevue, WA and focuses on owning core parts of the system that feeds planning workflows for 12 last-mile and sort-center business lines. You will build ETL pipelines, data models, and data quality processes, and contribute to how AI agents generate, validate, and execute data operations.

What you’ll do

• Design and own logical and physical data models for major datasets, creating coherent models that support physical design and multiple downstream consumers.
• Build and optimize ETL pipelines for complex datasets using Amazon Redshift, S3, EMR, AWS Glue, Lambda, and Athena, orchestrated with Airflow/MWAA and Python for solutions that are testable, maintainable, and efficient.
• Own configuration-driven data frameworks that replace repetitive custom code with reusable, declarative patterns for ingestion, transformation, and metric curation.
• Build AI agent tooling and MCP-based interfaces so conversational agents can generate SQL, validate configurations, manage data quality rules, and execute pipeline operations using natural language.
• Own ongoing data quality for datasets you build, including data contracts, defined SLAs, data certification processes, and automation of manual quality steps.
• Collaborate with planning scientists, software engineers, BI engineers, and product managers to balance customer needs with technical requirements.
• Improve self-service data access by building analytical data models and tooling that reduce dependency on the DE team for common access patterns.
• Improve engineering processes through automation of manual operations, monitoring and alerting standards, and code quality and dependency management practices.
• Mentor engineers and interns, training new team members on how team data solutions are constructed, operated, and aligned to the broader architecture.
• Participate in the interview process and help with recruiting for the team.

Requirements

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

Technologies

• Amazon Redshift, S3, EMR, AWS Glue, Lambda, Athena
• Python, Airflow, MWAA
• MCP, SQL, Oracle
• ETL/ELT, OLAP
• Kinesis, FireHose, IAM roles and permissions

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, and options 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
• Parental leave

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)

Salary: USD 132,100 - 178,800 per year. Experience level: Data Engineer II (minimum 3 years).