Amazon.com Services LLC
E-Commerce
DataEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Engineer at Amazon.com Services LLC. Skills: Data Engineering, SQL, Python. Design, build, and maintain scalable data pipelines. Develop and optimize data models”
Industry & Context.
Root cause analysis; Troubleshooting; Data-driven decision making
What They're Looking For.
Must Have
3+ years of experience in data engineering, Bachelor's degree in Computer Science, Engineering, or related field, Proficiency in SQL, Experience with Python
Nice to Have
Master's degree preferred, Experience with cloud platforms (AWS, GCP, Azure), Experience with data warehousing solutions, Experience with ETL/ELT processes, Experience with distributed data processing frameworks (e.g., Spark), Experience with machine learning frameworks, Experience with BI tools, Experience with CI/CD pipelines, Experience with containerization technologies (Docker, Kubernetes)
What You'll Do.
and maintain scalable data pipelines
Develop and optimize data models
Implement data quality checks and monitoring
Collaborate with data scientists and analysts
Build and manage ETL/ELT processes
Ensure data accuracy and reliability
Automate data-related tasks
Troubleshoot and resolve data issues
Contribute to data architecture decisions
Stay updated on emerging data technologies
How You'll Work.
Team & Collaboration
Cross-functional teams; Data scientists; Analysts; Software engineers
Process & Methodology
Agile methodologies
Full Job Description
Worldwide Grocery Store Tech (WWGST) is seeking a Data Engineer to join our Data & Analytics team. In this position, you will be responsible for architecting robust data infrastructures and developing advanced data pipelines to unlock the full potential of our expansive data landscape. Key job responsibilities - Help build the infrastructure that powers data-driven decision making. Utilize software engineering best practices, data management fundamentals, data storage principles, and recent advances in distributed systems. - Manage and optimize usage of cloud computing resources, particularly on AWS, to support data infrastructure. - Collaborate with Business Intelligence Engineers to establish best practices for data reporting, analysis, integrity, testing, validation, and documentation. - Collaborate with Data Scientists to implement advanced analytics algorithms that exploit our rich data sets for statistical analysis, prediction, clustering and machine learning. - Drive the architecture and technology decisions that enable a world-class user experience. - Develop in-depth knowledge of the Amazon's various data sources to determine the appropriate data resources for each use case. - Encourage the organization to adopt next-generation data architecture strategies, proposing both data flows and storage solutions - Thrive in an environment with a degree of ambiguity, quickly building proof of concepts, iterating, and improving data-driven solutions. - Create extensible designs and easy to maintain solutions with the long term vision in mind. - Have an understanding and empathy for business objectives, and continually align your work with those objectives and seek to deliver business value. About the team DASH Team is a cross-cutting data engineering team serving the broader WWGS organization and it is pioneering as an AI-first team, delivering analytics using AI in 2026.. DASH operates as a central hub for data infrastructure, consuming raw data, transforming it int
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