Data Engineer II , UTR Data Engineering

Amazon is a technology and e-commerce company building data infrastructure for labor planning across its last-mile and sort-center business lines. The Data Engineer II will own data architecture, build optimized ETL pipelines and reusable AI-powered data frameworks, improve data quality and self-service analytics, and collaborate with cross-functional teams while mentoring engineers and interns.

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

Preferred

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)

AWS

Amazon Redshift

Amazon S3

AWS Glue

Amazon EMR

Amazon Kinesis

Amazon Data Firehose

AWS Lambda

IAM Roles

Permissions

Non-Relational Databases

Object Storage

Document Stores

Key-Value Stores

Graph Databases

Column-Family Databases

Benefits

Sign-on payments

Restricted stock units (RSUs)

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

Parental leave

Company

Online retail and cloud computing services

Seattle, Washington, USA

https://amazon.com/

Founded in 1994

10001+ employees

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

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)

Required skills

Data Modeling, ETL/ELT, OLAP Technologies, SQL, Oracle, Data Warehousing, AWS Redshift, Amazon S3, AWS Glue, Amazon EMR, Amazon Kinesis, Amazon Kinesis Data Firehose, AWS Lambda, AWS IAM, Non-relational Databases

Experience

3+ years