Principal Software Engineer II - Next-Gen Data Transformations

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.

This role is not about building traditional data processing pipelines or legacy ETL/ELT workflows; it is about building the core distributed systems and atomic primitives that make those agentic workflows possible.

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. Our solid foundation supporting the seamless transition for enterprises between batch and streaming through Dynamic Tables, Streams & Tasks, and DBT Projects is the starting point.

Your architectural work will extend the reach of the core engine to accelerate and support the massive scale of the Snowpark and Spark ecosystems. You are building the systems that allow both data engineers and autonomous agents to process exabytes of data with sub-second state propagation and absolute transactional integrity across the Snowflake Data Cloud.

As a Principal Engineer II, you will own the technical vision for the Data Transformation umbrella of capabilities. Your work on streaming internals and declarative state management provides the architectural substrate for high-performance customer features processing. This foundational technology is engineered to drive low-latency, high-throughput data transformations at a massive scale to empower enterprises to build and scale complex applications, including autonomous agentic loops.

This infrastructure enables our broader ecosystem to operate on live, governed data, ensuring that the core engine primitives we build translate directly into superior data freshness and processing efficiency for every customer.

- 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.

- 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.

You will build the industry-leading Cloud Data and AI Platform. This is not just about maintaining a product; it is about innovating with rigor to solve the hardest problems in distributed systems.