Data Engineer: AI-Driven Pipelines & Multi-Agent Platform

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

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