Principal Software Engineer II - Next-gen Data Transformations

Snowflake Snowflake · Data AI · WA-Bellevue, United States · Engineering

Principal Software Engineer II to architect the core data processing engine of the Snowflake Data & AI Cloud, focusing on building distributed systems and atomic primitives for agentic workflows. This role involves designing and implementing stateful stream processing, incremental view maintenance, and distributed orchestration, enabling low-latency, high-throughput data transformations at scale for autonomous agentic loops and modern data processing.

What you'd actually do

  1. Architect Foundation Primitives for Agentic AI Data Engineering: Design the internal engines for Dynamic Tables, Streams, and Tasks, ensuring the underlying processing kernels provide the elastic, serverless foundation required for real-time agentic reasoning.
  2. Build the Data Transformation Processing Fabric: Develop the low-level infrastructure for automated triggers and incremental processing logic, allowing the Snowflake engine to proactively manage, optimize, and process incoming data without manual intervention.
  3. Innovate in System Internals: 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.
  4. Displace Legacy Orchestration Layers: Identify how to build superior, native processing capabilities directly within the Snowflake engine to eliminate the complexity of external schedulers, simplifying the architectural scaffolding for our customers.
  5. Engineer for Global Scale and Governance: Design and implement highly reliable, multi-tenant system internals that handle exabytes of data while maintaining Snowflake’s industry-leading standards for resource isolation, security, and distributed consistency.

Skills

Required

  • 14+ years of industry experience building database systems internals, distributed systems internals, or large-scale data processing engines.
  • Strong Technical Leadership: Operates as a broad architect, setting architectural direction, mentoring senior engineers, and establishing technical standards for large cross-product initiatives, coupled with exceptional ability to navigate organizational complexity, align multiple teams, and drive cross-functional decisions spanning multiple teams
  • Mastery of Systems Programming: Deep expertise in stateful stream processing, incremental view maintenance, distributed transactions, and query execution internals.
  • 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.
  • Distributed Systems Exper

What the JD emphasized

  • 14+ years of industry experience
  • Mastery of Systems Programming
  • Infrastructure-First Mindset

Other signals

  • agentic enterprise
  • AI-native thinkers
  • high-performance, unified compute fabrics
  • Autonomous agents require more than just models; they require a high-fidelity, low-latency state layer
  • building the core distributed systems and atomic primitives that make those agentic workflows possible
  • Stateful Stream Processing Engines
  • Incremental View Maintenance Engine
  • Distributed Orchestration Fabric
  • sub-second state propagation and absolute transactional integrity
  • low-latency, high-throughput data transformations at a massive scale
  • autonomous agentic loops
  • live, governed data
  • processing primitives
  • real-time agentic reasoning
  • proactively manage, optimize, and process incoming data without manual intervention
  • freshness-first system architecture
  • data is always ready for model consumption
  • native processing capabilities directly within the Snowflake engine
  • external schedulers
  • multi-tenant system internals
  • Model Context Protocol (MCP)
  • autonomous agent ecosystems
  • modern Python and Spark data processing workflows
  • massive-scale architectural challenges
  • operational readiness
  • reliability, availability, and performance
  • database systems internals
  • distributed systems internals
  • large-scale data processing engines
  • Systems Programming
  • stateful stream processing
  • incremental view maintenance
  • distributed transactions
  • query execution internals
  • Infrastructure-First Mindset
  • building the Operating System and the Engine rather than the application or the end-user pipeline
  • Distributed Systems Exper