Data Engineer , Ring Agent Platforms

Amazon; Madrid; Presencial; EUR 70.000 - 110.000; Jornada completa

Descripción de la vacante

Amazon Spain Services, S.L.U. is seeking a Data Engineer to design, build, and operate data pipelines, models, and platform infrastructure powering Ring's analytics, science, and AI initiatives.

You will own the end-to-end data lifecycle—from ingestion to delivery—ensuring analysts, scientists, and AI systems access reliable, well-structured data at scale, and you will use AI development IDEs and generative AI tooling to accelerate tasks and build multi-agent solutions that automate common data

Formación

• 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

Responsabilidades

• Design, build, and operate data pipelines, models, and platform infrastructure for analytics initiatives
• Own end-to-end data lifecycle from ingestion to delivery for reliable, well-structured data
• Contribute to shared data platform, tooling, and developer experience
• Leverage AI development IDEs and generative AI tooling to accelerate data engineering tasks

Conocimientos

Python

SQL

Data pipelines

Herramientas

Spark

Airflow

dbt

Descripción del empleo

Job ID: 10515924 | Amazon Spain Services, S.L.U.

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.

Basic Qualifications

• 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

Preferred Qualifications

• 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)

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