Amazon.com Services LLC

Business Intelligence, Data Engineering, operations

DataEngineerII,OTS-DataANCHORTeam

$100–179k Austin, Texas, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Data Engineer II, OTS - Data ANCHOR Team at Amazon.com Services LLC. Skills: Data engineering, Data infrastructure, AI/ML data infrastructure, ETL/ELT pipelines. Design production-grade ETL/ELT pipelines. Build production-grade ETL/ELT pipelines”

What You'll Achieve.

Deliver data products; Drive measurable business outcomes

Industry & Context.

Business Intelligence, Data Engineering, operations
Problems you'll solve

Data-driven decision making

What They're Looking For.

Must Have

3+ years of data engineering experience, 3+ years developing and operating large-scale data structures for BI analytics using ETL/ELT, 1+ years developing and operating large-scale data structures for BI analytics using SQL, Experience with data modeling, Experience with data warehousing, Experience building ETL pipelines, Experience with SQL, Experience with Python scripting, Experience in software development, Experience with data infrastructures, Bachelor's degree in Computer Science, Bachelor's degree in Computer Engineering, Bachelor's degree in Information Technology, Bachelor's degree in related fields

Nice to Have

Master's degree in computer science, Master's degree in engineering, Master's degree in analytics, Master's degree in mathematics, Master's degree in statistics, Master's degree in IT, Master's degree in equivalent

What You'll Do.

Design production-grade ETL/ELT pipelines

Build production-grade ETL/ELT pipelines

Maintain production-grade ETL/ELT pipelines

Design big data infrastructure

Build big data infrastructure

Maintain big data infrastructure

Build feature engineering workflows

Build ML-ready data pipelines

Contribute to data governance

Contribute to quality standards

Support implementation of GenAI solutions

Build semantic layers

Maintain semantic layers

Build dashboard data models

Maintain dashboard data models

Follow best practices for data engineering

Contribute to best practices for data engineering

How You'll Work.

Team & Collaboration

Solution Architects; Data Engineers; Applied Scientists; BIEs; Program Managers; BI teams; ML Engineers; Data Scientists; Operational stakeholders

Full Job Description

Join the OTS Data ANCHOR team to build strategic data infrastructure powering Amazon's Operations Technology ecosystem. Our team provides critical data infrastructure support for OpsTech IT, supporting Amazon's global customer commitment. You'll 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, and Amazon Campus. As a Data Engineer, you will build and maintain scalable data pipelines and AI/ML-ready data infrastructure that power AI-driven operational insights and Data Science initiatives across Amazon's global fulfillment and maintenance networks. You will design and implement ETL/ELT pipelines, build feature engineering workflows, and collaborate with Solution Architects, Data Engineers, Applied Scientists, and BIEs to deliver data products that drive measurable business outcomes. You will contribute to Data Ops and AI intelligent data practices — including data versioning, pipeline monitoring, and model retraining data support — and help establish engineering best practices within the team. This role directly enables the team's mission to implement GenAI solutions for automated reporting, diagnostics, and predictive and prescriptive analytics across worldwide operations. This is a high-impact individual contributor role with significant opportunity to grow technical scope and organizational influence at the intersection of data engineering, Data Science, and AI. Key job responsibilities - Design, build, and maintain production-grade ETL/ELT pipelines and big data infrastructure supporting OTS operational intelligence. - Build feature engineering workflows and ML-ready data pipelines that support Data Science experimentation and production model serving. - Contribute to data governance and quality standards across analytical and ML data products. - Support implementatio

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