Data Engineer II , UTR Data Engineering

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. We are shifting from hand-coded, custom pipelines to an AI-native approach, building reusable frameworks where engineers and business users define needs through configurations and natural language instead of custom code. AI agents handle orchestration, validation, and deployment. This transformation is early-stage, so you will help define how we build, what patterns we standardize, and how AI fits into data engineering workflows.

Responsibilities

• Design and own logical and physical data models for major datasets in the team's architecture, creating 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), ensuring solutions are 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.
• 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 by implementing standardized data contracts, defining SLAs, establishing data certification processes, and automating manual quality processes.
• Collaborate with planning scientists, software engineers, BI engineers, and product managers to balance customer requirements with technical requirements, shaping what we build, not just how.
• Improve self-service access to data by building analytical data models and tooling that reduce dependency on the DE team for common data access patterns.
• Enhance engineering processes by automating manual operations, establishing monitoring and alerting standards, and driving code quality and dependency management practices.
• Mentor engineers and interns, train new team members on data solutions, and participate in the interview process to help recruit for the team.

Requirements

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

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).

Pay

USA, WA, Bellevue - $132,100.00 - $178,800.00 USD annually. Your package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on experience, qualifications, and location.

Benefits

• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, and optional supplemental life plans).
• Employee Assistance Program (EAP) and mental health support.
• Medical Advice Line and Flexible Spending Accounts.
• Adoption and Surrogacy Reimbursement coverage.
• 401(k) matching.
• Paid time off and parental leave.

Learn more about our benefits at amazon.jobs/en/benefits.