Snowflake의 Dynamic Tables 성능 팀을 이끌 Staff Software Engineer를 채용합니다. 대규모 데이터 시스템 최적화 및 쿼리 엔진 설계에 10년 이상의 경력을 보유한 전문가를 찾습니다. C++ 또는 Java 숙련도와 분산 시스템 설계 역량이 필수이며, 기술 로드맵 수립 및 팀 멘토링을 통해 제품의 성능과 확장성을 주도하게 됩니다.
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.
The Dynamic Tables performance team is responsible for making incremental refresh fast, predictable, and cost-efficient across increasingly complex query shapes. As a Staff Engineer on this team, you will own the technical direction for critical performance initiatives and be a force multiplier for the engineers around you.
Lead the design and implementation of performance improvements to the incremental view maintenance engine, including multi-join incrementalization, novel incrementalization semantics, incremental window functions, and stacked operations.
Help define the roadmap for the incremental view maintenance engine, identifying key performance, scalability, and correctness milestones, prioritizing high-impact enhancements, and aligning technical investments with product and research goals.
Collaborate across teams to co-design improvements that benefit incremental pipelines.
Mentor engineers, drive design reviews, and raise the technical bar for the team through architectural leadership and high-quality code.
Contribute to the research and publication roadmap; the team has an active presence at top-tier database conferences (SIGMOD, VLDB).
10 + years of experience building and optimizing large-scale data systems, with deep expertise in at least one of: query optimization, incremental/stream processing, or materialized view maintenance.
Strong computer science fundamentals — algorithms, data structures, and distributed systems design.
Proficiency in C++ or Java; experience with systems-level performance analysis (profiling, benchmarking, regression detection).
Demonstrated ability to lead multi-engineer, cross-team technical initiatives and translate ambiguous problem spaces into concrete engineering plans.
Experience operating systems at cloud scale (multi-tenant SaaS, petabyte-scale data, thousands of concurrent workloads).
Strong written and verbal communication skills; ability to present complex technical trade-offs to both engineering and product audiences.
Experience with a major analytical DBMS (BigQuery, Redshift, Databricks, Teradata, Oracle, SQL Server).
Familiarity with stream processing algorithms.
Experience with CDC pipelines, data lake architectures (Iceberg, Delta), or the broader data engineering ecosystem (dbt, Airflow, Fivetran).
Advanced degree (MS or PhD) in Computer Science, with emphasis on database systems.
Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
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 benefits information: careers.snowflake.com
