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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer , Ring Agent Platforms - **Company:** Amazon.com, Inc. - **Location:** Spain - **Contract:** Internship / Graduate position - **Skills:** Artificial Intelligence, Airflow, Code Review, Continuous Integration, Data as a Services, Information Engineering, Data Governance, Data Sharing, Data Warehousing, Programming Tools, Python (Programming Language), Machine Learning, Cloud Services, Software Engineering, SQL Databases, Data Streaming, Datadog, Data Logging, Multi-Agent Systems, Apache Spark, Generative AI, Data Layers, AI Platforms, Core Data, Data Lineage, Virtual Agents, Software Version Control, Data Pipelines, Serverless Computing - **Published:** August 28, 2026 - **Apply:** https://www.amazon.jobs/applicant/jobs/10515924/apply ## About the Role Non-internship professional experience in data engineering or a closely related discipline - Experience building and operating data pipelines (batch and/or streaming) using frameworks such as Spark, Airflow, dbt, or equivalent - Proficiency in Python and SQL - Experience with cloud-native data services including data warehouses, object storage, event streaming, and serverless compute - Familiarity with data modeling and data quality practices - Experience with software development life cycle practices including code reviews, source control, CI/CD, testing, and operational support - Demonstrated use of generative AI tools (e.g., agentic coding assistants, AI-powered IDEs) in a professional or project setting, Experience designing or building AI agents or multi-agent solutions that automate engineering workflows - Familiarity with agentic AI patterns including tool use, function calling, and multi-agent orchestration - Familiarity with at least one agentic AI development IDE - Experience building or maintaining shared data models, semantic layers, or data contracts - Familiarity with data governance, cataloging, or lineage tracking - Experience contributing to shared platform infrastructure, developer tooling, or self-service data services - Familiarity with observability tooling for data pipelines (logging, metrics, alerting) ## Description We are looking for a Data Engineer to design, build, and operate the data pipelines, models, and platform infrastructure that power Ring's analytics, science, and AI initiatives. You will own the end-to-end data lifecycle - ingestion, transformation, modeling, quality enforcement, and delivery - ensuring that analysts, scientists, and AI systems have access to reliable, well-structured data at scale. You will use AI development IDEs and generative AI tooling daily to accelerate your work, and you will build multi-agent solutions that automate common data engineering tasks - pipeline generation, data quality enforcement, testing, and operational response. The goal is to turn repeatable patterns into agent-driven workflows that raise velocity and consistency across the team. You will also contribute to the shared data platform when needed - improving developer tooling, maintaining infrastructure, and supporting the services that the broader data org depends on. About the team The Data and Agents Organization spans data engineering, business intelligence, applied science, and agentic AI. The org is structured into three primary groups: one focused on core data platforms, tooling, and pipeline infrastructure; another focused on AI/ML models, business analytics, shared data models, product analytics, and strategic science initiatives; and a third focused on building a multi-agent AI platform that enables teams to compose, deploy, and orchestrate autonomous AI agents at scale. Capacity is balanced across direct business support, strategic new development, and operational health. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Debugging in the Dark](https://www.wearedevelopers.com/videos/1658-debugging-in-the-dark) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Software Engineering Social Connection: Yubo’s lean approach to scaling an 80M-user infrastructure](https://www.wearedevelopers.com/videos/1583-software-engineering-social-connection-yubo-s-lean-approach-to-scaling-an-80m-user-infrastructure) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)