Snowflake powers AI, data engineering, applications, and analytics on a trusted, scalable AI Data Cloud—eliminating silos and accelerating innovation. Backed by Sequoia.
About the role
Define and drive the technical direction for Snowflake's core data engineering and streaming transformation primitives, spanning Streams, Tasks, Dynamic Tables, and adjacent pipeline constructs. Identify and lead multi-quarter technical investments — performance, scalability, correctness, and reliability — translating ambiguous problem spaces into concrete engineering plans with measurable outcomes.
What they're looking for
- 15+ years of experience designing, building, and operating large-scale distributed data systems
- Deep expertise in at least one core area: stream processing, declarative query execution, pipeline orchestration, or data transformation at scale
- Strong computer science fundamentals — distributed systems, algorithms, fault tolerance, and consistency models
- Proficiency in C++ or Java, comfort with systems-level reasoning (latency, throughput, resource efficiency at cloud scale)
- Demonstrated ability to lead cross-team technical initiatives from blank-page architecture through production at petabyte scale across thousands of concurrent workloads
- Strong written and verbal communication skills, ability to represent complex technical trade-offs clearly to engineering, product, and leadership audiences
More about this role
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. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
Data pipelines are foundational infrastructure — when they're fast, correct, and maintainable, customers build on them with confidence. If you've spent the bulk of your career building large-scale data infrastructure — designing streaming or transformation primitives, reasoning hard about consistency and fault tolerance, and owning the systems that run under millions of customer workloads — this role might be for you. You'll be working on the pipeline layer at Snowflake: the constructs...
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