Principal Software Engineer (Next-Gen Data Transformations)

Join Snowflake, a leading data cloud company, as a Principal Software Engineer. In this role, you will architect the core data processing engine of the Snowflake Data & AI Cloud, focusing on building the fundamental transformations infrastructure and driving technical strategy for the AI era. You will work on stateful stream processing, incremental view maintenance, and distributed orchestration, while ensuring operational excellence and customer success.

• Architect the core data processing engine of the Snowflake Data & AI Cloud, focusing on building the core distributed systems and atomic primitives for agentic workflows.
• Design and implement the fundamental transformations infrastructure, including Stateful Stream Processing Engines, Incremental View Maintenance Kernels, Materialization Internals, and the Distributed Orchestration Fabric.
• Drive the long-term roadmap for stateful streaming, moving the industry toward a freshness-first system architecture where data is always ready for model consumption.
• 14+ years of industry experience building database kernels, distributed systems internals, or large-scale data processing engines
• Agent-Native Vision: A clear understanding of how the Engine must evolve to support autonomous agentic loops, including low-latency context injection and stateful memory for LLM-driven applications
• Mastery of Systems Programming: Deep expertise in stateful stream processing, incremental view maintenance, distributed transactions, and query execution internals
• Distributed Systems Expertise: Proven track record of solving complex problems in consensus, replication, and high-concurrency environments at cloud scale
• Infrastructure-First Mindset: You are a systems builder. You prefer building the Operating System and the Engine rather than the application or the end-user pipeline
• Collaborative Leadership: Ability to work in a globally distributed environment, collaborate across product and engineering boundaries, and mentor senior and junior engineers alike
• Ecosystem Awareness: A deep understanding of the architectural limitations of traditional tools like Airflow or dbt, and a vision for how to solve those challenges through native Snowflake system design
• Database Internals: Direct experience developing query optimizers, storage engines, or transaction managers
• Streaming Ecosystem Internals: Deep knowledge of the internal workings of Flink, Beam, or Spark Streaming and their limitations in a multi-tenant cloud environment
• Autonomic Infrastructure: Experience building zero-ops infrastructure services or self-healing distributed systems for public clouds