Senior Data Engineer, Ring Data Platform

Data Engineer

Come build the future of smart security with us. Are you excited about shaping the future of devices and services that keep people close to what's important? Ring's Decision Sciences Platform Team is looking for an experienced Data Engineer who is passionate about building scalable data and AI platform capabilities to accelerate innovation across the company. This role is critical in scaling our AI & Data Platform, which serves as the foundational layer for Ring's growing Artificial Intelligence and Machine Learning initiatives. You will play a key role in ensuring the platform meets the demands of AI/ML model training, evaluation, and serving, enabling Ring to deploy AI across the full application lifecycle. An ideal individual is someone who has deep data engineering skills around ETL, data modeling, database architecture and big data solutions. You should have strong business judgement, excellent written and verbal communication skills.

Key job responsibilities:

• Design, build, and maintain robust data pipelines and AI integration solutions using AWS-native services and/or internal Amazon tooling.
• Build and support scalable ingestion, transformation, and serving layers that power AI/ML workflows, including Generative AI and Agentic AI systems.
• Collaborate closely with data scientists, software engineers, and product managers to deploy AI-first capabilities in customer-facing and internal applications.
• Improve and maintain existing data workflows to meet evolving compliance, security, and performance standards.
• Develop frameworks and tools to enable self-service access to data and AI assets across the organization.
• Conduct code reviews, enforce best practices for ETL and data hygiene, and drive engineering excellence across the team.
• Document architecture, designs, and operational processes to ensure scalability, reliability, and knowledge sharing.
• Stay current with advances in GenAI, Agentic AI, cloud-native AI platforms, and data engineering best practices.