Engineering Manager - Feature Store

Engineering Manager - Feature Store Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level. BUILD THE FUTURE OF THE AI DATA CLOUD. Snowflake’s Feature Store is a core component of our Machine Learning platform, enabling customers to build, manage, and serve machine learning features directly within the Snowflake Data Cloud. It powers both offline training and low-latency online inference, supporting batch and streaming pipelines at enterprise scale while maintaining Snowflake’s standards for governance, reliability, and performance. We are looking for a highly technical Engineering Manager to lead the development of real-time and online serving infrastructure that enables production ML workloads for global enterprises. ABOUT THE ROLE As an Engineering Manager on the Feature Store team, you will lead a team building distributed systems that power feature computation, storage, and low-latency serving. You will work at the intersection of large-scale data infrastructure and real-time ML systems, ensuring that features are computed reliably and served consistently between training and inference workflows. You will partner closely with Product, Snowpark, ML Platform, and core infrastructure teams to deliver customer-facing capabilities that support mission-critical AI applications. This role requires strong technical depth in distributed systems and real-time data platforms, combined with a proven ability to lead teams and ship high-quality products. AS AN ENGINEERING MANAGER, YOU WILL: - Lead and grow a team responsible for online feature serving and real-time feature infrastructure. - Drive the design and delivery of distributed systems supporting low-latency, high-throughput feature access for inference workloads. - Shape architecture for streaming pipelines and stateful processing systems that ensure freshness and consistency of ML features. - Own execution of customer-facing features from design through production rollout. - Partner cross-functionally to translate enterprise ML requirements into scalable technical solutions. - Establish strong engineering practices around performance optimization, observability, reliability, and operational excellence. - Contribute hands-on to architecture reviews and critical technical decisions. OUR IDEAL CANDIDATE WILL HAVE: - 8+ years of experience building distributed systems, data infrastructure, or backend platform services. - 3+ years of engineering management experience leading high-performing teams. - Strong background in distributed systems fundamentals, including scalability, fault tolerance, consistency, and performance tuning. - Experience building or operating low-latency, real-time, or online serving systems. - Experience with large-scale data infrastructure and streaming systems. - Exposure to machine learning systems, feature engineering workflows, or model serving infrastructure. - Demonstrated track record of shipping customer-facing platform products at scale. - Experience operating highly available, multi-tenant cloud services. - Strong communication skills and the ability to collaborate across engineering and product teams. The Feature Store sits at the intersection of distributed systems, real-time serving, and machine learning infrastructure. In this role, you will help define how enterprises serve high-quality features for AI applications with low latency and high reliability — directly within the Snowflake Data Cloud. Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confid ... (truncated, view full listing at source)