| Location | Austin, TX |
| Industry | Retail |
| Company Size | 10,000 employees or more |
| Year Founded | 1994 |
| Website | http://Amazon.com/militaryroles |
Join OpsTech to build strategic data infrastructure powering Amazon's global operations technology ecosystem. OpsTech provides critical technology and data capabilities that support Amazon's customer commitment worldwide. You will work at the intersection of large scale data processing and real world operational impact, creating intelligence that directly influences how Amazon fulfills millions of orders across fulfillment centers, Amazon Fresh, Prime Now, Lockers, Pantry, Amazon Campus, and other operational environments.
As a Data Engineer, you will build and evolve scalable data platforms that power analytics, machine learning, and AI driven experiences across Amazon's global fulfillment and maintenance networks. You will design high performance data pipelines, create trusted data products, and work with Solution Architects, Data Engineers, Applied Scientists, and Business Intelligence Engineers to turn complex operational data into intelligence that can be used by both people and AI systems.
You will help shape modern data engineering practices across OpsTech, including automated data quality, observability, lineage, data contracts, orchestration, and intelligent pipeline operations. Your work will provide the trusted data foundation behind AI agents, machine learning systems, operational analytics, and automated decision making at global scale.
This is a high impact individual contributor role with significant opportunity to expand your technical scope and influence how OpsTech builds the next generation of data and AI capabilities.
Key job responsibilities
A day in the life
You will work closely with Data Engineers, Data Scientists, ML Engineers, Business Intelligence Engineers, Solution Architects, Program Managers, and operations teams across OpsTech.
Your day may include designing a new data pipeline, reviewing architecture for an AI powered application, improving the reliability of a critical dataset, or working with partners to understand an operational problem and turn it into a scalable data solution.
You will spend time building and improving data products used by analysts, operators, leaders, machine learning systems, and AI agents. You may investigate data quality issues, optimize large scale processing workflows, improve observability, or develop new semantic models that make complex operational data easier to understand and use.
You will also participate in design reviews, code reviews, technical discussions, and planning sessions while owning projects from initial problem definition through production launch.
The problems are varied, technically challenging, and directly connected to how Amazon operates at global scale.