Data Engineer , Ring Agent Platforms

Amazon is hiring a Data Engineer , Ring Agent Platforms in Madrid, Spain. Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this data engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
Tools and skills the posting cites include Spark, Airflow and dbt.
Level classifies it as a senior role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Design and operate data pipelines and multi-agent solutions for Ring's analytics, science, and AI initiatives using generative AI tooling.

SparkAirflowdbtPythonSQLGenerative AI

ai-agentsdata-engineeringdata-pipelinesdata-modelingmulti-agent-systems

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)

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.

How we rate this

Data Engineer , Ring Agent Platforms at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Engineer , Ring Agent Platforms is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in ES, M, Madrid.
The job was posted on August 26, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsData EngineeringData PipelinesData ModelingMulti Agent SystemsSparkAirflowdbt

Also common in data engineer jobs at this level

AWS Databricks Machine learning Azure Snowflake Java

Pay

Typical data engineer job: $145k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where data pipelines was part of your work. What did you do?
Tell me about a project where data modeling was part of your work. What did you do?
Tell me about a project where multi agent systems was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI agents, Data Engineering, Data Pipelines, Data Modeling, and Multi Agent Systems. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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