Amazon Spain Services, S. L. U.
Software Development, Data Engineering, alexa and amazon devices
DataEngineeringManager,RingAgentPlatforms
Neural analysis suggests this role is
optimal for Manager candidates.
“Data Engineering Manager, Ring Agent Platforms at Amazon Spain Services, S. L. U.. Skills: Data Engineering, Team Management, AI Engineering, Agentic Tooling. Lead data engineering team. Build data pipelines”
Industry & Context.
Root cause analysis; Troubleshooting
What They're Looking For.
Must Have
Engineering team management experience, Hands-on data engineering experience, Data platform and pipeline delivery experience, Data systems design or architecture experience, Data modeling experience, Pipeline patterns experience, Reliability experience, Scaling strategies experience, Data pipelines development experience, Cloud-native data infrastructure development experience, Engineering practices knowledge, Full software development life cycle knowledge, Coding standards knowledge, Code reviews knowledge, Source control knowledge, CI/CD knowledge, Testing knowledge, Operational excellence knowledge, Partnering with product management experience, Partnering with applied science experience, Partnering with cross-functional stakeholders experience, Translate business needs to technical roadmaps experience
Nice to Have
Big data technologies experience, AWS Tools and Technologies experience, Generative AI tools experience, AI development IDEs experience, Multi-agent solutions familiarity, Agentic AI development IDE familiarity, Shared data models experience, Semantic layers experience, Data contracts experience, Data governance familiarity, Data cataloging familiarity, Data lineage tracking familiarity, Shared platform infrastructure experience, Developer tooling experience, Self-service data services experience
What You'll Do.
Lead data engineering team
Operate data pipelines
Build platform infrastructure
Operate platform infrastructure
Own data platform delivery
Own operational health
Build high-performing team
Mentor high-performing team
Drive adoption of AI practices
Guide evolution of tooling
Develop fluency with agentic tooling
Maintain data engineering fundamentals
Partner with business intelligence teams
Partner with applied science teams
Partner with product teams
Contribute to shared infrastructure
How You'll Work.
Team & Collaboration
Cross-functional stakeholders; Business intelligence teams; Applied science teams; Product teams
Process & Methodology
Technical roadmaps
Full Job Description
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. 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: - Experience in engineering team management - Experience working directly within data engineering or closely related teams, with hands-on contribution to data platform and pipeline delivery - Experience designing or architecting data systems, including data modeling, pipeline patterns, reliability, and scaling strategies -
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