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# Data Engineer I, AWS WW Field Enablement, Analytics and Product Operations

- **Company:** Amazon.com, Inc.
- **Location:** Arlington, VA, United States
- **Experience:** Experienced
- **Salary:** $101,300.0 - $160,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Data Analysis, Big Data, Code Review, Extract Transform Load (ETL), Data Systems, Data Visualization, Relational Databases, IBM InfoSphere DataStage, Distributed Systems, Apache Hadoop, MapReduce, Apache Hive, IBM Cognos Business Intelligence, NoSQL, Oracle (Applications), Query Optimization, Software Construction, Software Engineering, Tableau (Software), Data Storage Technologies, Apache Spark, Electronic Medical Records, Information Technology, Build Process, Software Coding, Amazon Redshift
- **Published:** May 15, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f98959243c620205

## About the Role

* 2+ years of data engineering experience
 * Experience with data modeling, warehousing and building ETL pipelines
 * Bachelor's degree or above in a quantitative/technical field such as computer science, engineering, statistics
 * Knowledge of basics of designing and implementing a data schema like normalization, relational model vs dimensional model
 * Knowledge of software engineering best practices across the development life cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations, * Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
 * Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
 * 4+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
 * Knowledge of AWS Infrastructure
 * Knowledge of BI analytics, reporting or visualization tools like Tableau, AWS QuickSight, Cognos or other third-party tools

## Description

* Design, build, and optimize logical data models and data pipelines for complex datasets
 * Own ongoing data quality and create self-service access to datasets for business intelligence, AI based tools and Model Context Protocols (MCP)
 * Improve metadata for better AI results
 * Collaborate with Program Managers, Technical Program Managers and other Data Engineers to design stable, performant data solutions
 * Write secure, stable, testable, and maintainable code with minimal defects
 * Apply appropriate data design approaches and make judicious trade-offs without over-engineering
 * Optimize resource usage including system hardware, data storage, query optimization, and AWS infrastructure
 * Participate actively in code reviews, design discussions, and team planning
 * Resolve root causes of complex problems and balance customer requirements with team needs
 * Stay current on distributed systems technologies (MapReduce, MPP architectures, NoSQL databases)


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