engineering
Posted Jun 24Prinicpal Software Engineer - Streaming Primitives
at Snowflake
On-site
Responsibilities
- BUILD CORE DATA ENGINEERING PRIMITIVES AT CLOUD SCALE Data pipelines are foundational infrastructure — when they're fast, correct, and maintainable, customers build on them with confidence.
Requirements
- 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.
- You'll be working on the streaming and transformation layer at Snowflake: the constructs that define how customers move, shape, and maintain data.
- AI has a real presence in this work — in how customers use these pipelines and in how we think about building them — but the core job is hard distributed systems engineering, and that's what we're hiring for.
- ABOUT THE TEAM We build the core data engineering primitives that power Snowflake's streaming and transformation capabilities.
- WHAT YOU'LL DO - 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.
- - 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.
- Experience with a major analytical DBMS (Snowflake, BigQuery, Redshift, Databricks, Teradata). - Hands-on background in streaming or event-driven systems (Flink, Kafka, Spark Structured Streaming). - Familiarity with the broader data engineering ecosystem: dbt, Airflow, Fivetran, Iceberg, Delta Lake. -
- Experience with CDC, change propagation, or incremental computation patterns. - Advanced degree (MS or PhD) in Computer Science, with emphasis on database or distributed systems.
- Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth.
Experience
- WHAT WE'RE LOOKING FOR - 15+ years of
Benefits
- How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and
Contact
- benefits information: careers.snowflake.com http://careers.snowflake.com
Additional details
- At Snowflake, we are powering the era of the agentic enterprise.
- 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.
- 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.
- From the constructs customers use to define real-time pipelines to the execution fabric that makes those pipelines reliable and cost-efficient at cloud scale, our team owns the full stack of declarative data engineering.
- We're a small, high-ownership team operating close to the product — which means your decisions ship, your architecture matters, and your fingerprints are on some of the most-used features in Snowflake's data engineering portfolio.
- - Identify and lead multi-quarter technical investments — performance, scalability, correctness, and reliability — translating ambiguous problem spaces into concrete engineering plans with measurable outcomes.
- - Partner with product, research, and peer engineering teams to co-design primitives that compose cleanly across the data engineering stack.
- - Operate as a force multiplier: run architectural reviews, set the technical bar for design documents, and help engineers grow through high-quality feedback and sponsorship.
- - Work directly with customers and field teams to understand real-world usage patterns; use that signal to prioritize what matters next.
- - Contribute to Snowflake's technical reputation — through internal design influence, external talks, or research publications in the data engineering space.