Description
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work.
We are hiring a Principal Engineer II to architect the core data processing engine of the Snowflake Data & AI Cloud. At Snowflake, we believe that high-performance, unified compute fabrics are the indispensable building blocks for Agentic AI. Autonomous agents require more than just models; they require a high-fidelity, low-latency state layer to reason, act, and persist context.
In this role, you will be a lead architect of the Snowflake Data Transformation Engine. You will design and implement the fundamental transformations infrastructure,Stateful Stream Processing Engines, Incremental View Maintenance Engine, Materialization Internals, and the Distributed Orchestration Fabric.
AS A PRINCIPAL SOFTWARE ENGINEER II AT SNOWFLAKE YOU WILL:
- 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.
- 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.
- 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.
- 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.
- 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.
- Drive Technical Strategy for the AI Era: Provide technical leadership to senior management and multiple departments, influencing how Snowflake’s core compute fabric evolves to support the burgeoning Model Context Protocol (MCP), autonomous agent ecosystems and modern Python and Spark data processing workflows.
- Drive Customer Success through Direct Engagement: Partner with Snowflake’s most strategic customers and field engineering teams to translate massive-scale architectural challenges into core engine requirements, ensuring our processing primitives meet the real-world demands of the global Data Cloud.
- Ensure Operational Excellence: Take responsibility for the operational readiness of the services, meeting the strict commitments to our customers regarding reliability, availability, and performance.
OUR IDEAL PRINCIPAL SOFTWARE ENGINEER II WILL HAVE:
- 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 Expertise: Proven track record of solving complex problems in consensus, replication, and high-concurrency environments at cloud scale.
- Ecosystem Awareness: A deep understanding of the architectural limitations of traditional orchestration and data processing tools, and a vision for how to solve those challenges through native Snowflake system design.
- Collaborative Leadership: Ability to work in a globally distributed environment, collaborate across product and engineering boundaries, and mentor senior and junior engineers alike.