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Nice to have
- Engineering team management experience, including hiring, performance management, and career development
- Working directly within data engineering or closely related teams, with hands-on contribution to data platform and pipeline delivery
- Designing or architecting data systems, including data modeling, pipeline patterns, reliability, and scaling strategies
- Experience building or leading development of data pipelines and cloud-native data infrastructure (e.g., data warehouses, data lakes, event-driven architectures, orchestration platforms)
- Knowledge of engineering practices across the full software development life cycle, including coding standards, code reviews, source control, CI/CD, testing, and operational excellence
- Experience partnering with product management, applied science, or cross-functional stakeholders to translate business needs into technical roadmaps
- Experience leading teams that use generative AI tools and AI development IDEs to accelerate engineering work
- Familiarity with multi-agent solutions that automate data engineering workflows (pipeline generation, data quality, testing, operational response)
- Familiarity with at least one agentic AI development IDE
- Experience building or overseeing shared data models, semantic layers, or data contracts
- Familiarity with data governance, cataloging, or lineage tracking practices
- Experience contributing to or overseeing shared platform infrastructure, developer tooling, or self-service data services
- Familiarity with observability tooling for data pipelines and data platform operations
We are looking for a Manager of Data Engineering to lead a team of data engineers building and operating the data pipelines, models, and platform infrastructure that power Ring's analytics, science, and AI initiatives. You will own the delivery and operational health of the data platform, build and mentor a high-performing team, and drive the adoption of AI-assisted engineering practices across the group.
Your team will use AI development IDEs and generative AI tooling daily, and will build multi-agent solutions that automate common data engineering tasks — pipeline generation, data quality enforcement, testing, and operational response. You will guide this evolution, helping your engineers develop fluency with agentic tooling while maintaining the data engineering fundamentals that everything depends on.
You will also partner with business intelligence, applied science, and product teams to translate data needs into technical roadmaps, and contribute to shared platform infrastructure when the work calls for it.
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 Agent Platform 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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