Data Engineering Manager, Ring Agent Platforms
Summary
The Data Engineering Manager will lead a team responsible for building and maintaining data pipelines, models, and platform infrastructure for Ring's analytics and AI initiatives. The role focuses on driving the adoption of generative AI and multi-agent systems to automate data engineering tasks while mentoring a high-performing team.
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 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.
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 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.