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- 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)
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.
Online application
Assessments
Online test · Not every role
Role-specific online assessments where the role requires them.
Phone screening
Phone call · Not every role
If you meet the basic qualifications you may be asked to complete a phone screening.
Interview loop
With current employees
Individual interviews with current employees, each assessing different aspects of your skills and experience; in person or remote.
Amazon is a global technology company focused on e-commerce, cloud computing, digital streaming, and artificial intelligence. It is one of the world's largest employers and operates a vast network of fulfillment centers, data centers, and corporate offices across the globe. In Spain, Amazon has a significant presence with corporate offices in Madrid and Barcelona, as well as numerous fulfillment and data center facilities, including in Huesca and other regions. The company is known for its customer-centric culture, innovation, and fast-paced work environment, offering a wide range of roles from engineering and operations to corporate and creative positions.
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.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Amazon · Madrid
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