Requirements

14+ years of software engineering experience with deep expertise in distributed systems.
Demonstrated track record of defining and delivering platform-scale technical initiatives.
Expert-level knowledge of streaming and/or batch data systems (Flink, Spark, or equivalent), with specialized knowledge in incremental materialization algorithms.
Strong systems thinking — ability to reason across layers of complexity (infra, storage, compute, API).
A passion for engaging directly with customers to gain insight and inspiration.
Experience influencing technical direction across organizations.
Excellent written and verbal communication for technical and executive audiences.

Desirable

Experience with AI-augmented development practices and integrating LLM-based tooling into engineering workflows.
Familiarity with Snowflake platform internals or cloud-native data systems.
Experience with metadata systems, query optimization, or data catalog infrastructure.
Contributions to open source, such as top-level Apache projects.

Drive the technical strategy and architecture for key Data Platform initiatives, focusing heavily on real-time data movement and incremental processing.
Lead design reviews and set engineering standards across teams.
Identify and resolve high-impact technical challenges and systemic bottlenecks to reduce latency and improve the efficiency of dynamic tables at cloud scale.
Mentor and grow senior engineers; raise the engineering bar.
Partner closely with product and infrastructure leadership on roadmap and direction.
Continuous hands-on technical deliverables in the most critical areas.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth.
We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.