Data Engineer II: AI-Driven Ops Analytics & Pipelines

Amazon; Austin (TX); On-site; USD 132,000 - 179,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Job summary

Amazon.com Services LLC is seeking a Data Engineer to design and maintain scalable ETL/ELT pipelines powering OpsTech IT. You will build ML-ready data infrastructure, collaborate with data scientists and engineers, and contribute to GenAI-driven reporting and analytics across Amazon’s global operations.

The role emphasizes end-to-end project delivery, data governance, and implementing best practices in data engineering, with opportunities to grow the technical scope and influence within the

Qualifications

• 3+ years of data engineering experience.
• 3+ years of ETL/ELT development and operations for BI analytics.
• 1+ years of SQL experience in BI analytics.
• Experience with data modeling, warehousing and building ETL pipelines.
• Experience delivering end-to-end projects independently.

Responsibilities

• Design and maintain production-grade ETL/ELT pipelines and big data infrastructure.
• Build feature engineering workflows and ML-ready data pipelines.
• Contribute to data governance and quality standards.
• Support GenAI solutions for automated reporting, diagnostics, and analytics.
• Build semantic layers and dashboard data models for worldwide operations.
• Collaborate with cross-functional teams to prioritize work.
• Follow best practices for code reviews, testing, monitoring, and documentation.

Skills

Data engineering

ETL/ELT

SQL

Data modeling

End-to-end projects

Education

Master's degree in CS/engineering or analytics

Tools

Python

Java

C++

Kafka

Kinesis

Flink

Storm

Beam

Job description

Amazon.com Services LLC is seeking a Data Engineer to design and maintain scalable ETL/ELT pipelines powering OpsTech IT. You will build ML-ready data infrastructure, collaborate with data scientists and engineers, and contribute to GenAI-driven reporting and analytics across Amazon’s global operations.

The role emphasizes end-to-end project delivery, data governance, and implementing best practices in data engineering, with opportunities to grow the technical scope and influence within the