Snowflake
Data Engineering
StaffSoftwareEngineer—DynamicTables,Performance
Neural analysis suggests this role is
optimal for Lead candidates.
“Staff Software Engineer — Dynamic Tables, Performance at Snowflake. Skills: large-scale data systems optimization, query optimization, incremental/stream processing, materialized view maintenance, distributed systems design, C++, systems-level performance analysis. Lead the design and implementation of performance improvements to the incremental view maintenance engine. Help define the roadmap for the incremental view maintenance engine”
What You'll Achieve.
make incremental refresh fast, predictable, and cost-efficient across increasingly complex query shapes; own the technical direction for critical performance initiatives; be a force multiplier for the engineers around you; identify key performance, scalability, and correctness milestones; raise the technical bar for the team through architectural leadership and high-quality code
Industry & Context.
solve problems and accelerate your impact; translate ambiguous problem spaces into concrete engineering plans
What They're Looking For.
Must Have
10 + years of experience building and optimizing large-scale data systems, deep expertise in at least one of: query optimization, incremental/stream processing, or materialized view maintenance, computer science fundamentals — algorithms, data structures, and distributed systems design, Proficiency in C++ or 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), written and verbal communication ability to present complex technical trade-offs to both engineering and product audiences
Nice to Have
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
What You'll Do.
Lead the design and implementation of performance improvements to the incremental view maintenance engine
Help define the roadmap for the incremental view maintenance engine
Contribute to the research and publication the team has an active presence at top-tier database conferences (SIGMOD
How You'll Work.
Team & Collaboration
Collaborate across teams to co-design improvements that benefit incremental pipelines; Mentor engineers; drive design reviews; raise the technical bar for the team through architectural leadership and high-quality code; Demonstrated ability to lead multi-engineer, cross-team technical initiatives; present complex technical trade-offs to both engineering and product audiences
Communication Scope
written and verbal communication ability to present complex technical trade-offs to both engineering and product audiences
Process & Methodology
translate ambiguous problem spaces into concrete engineering plans, prioritizing high-impact enhancements, aligning technical investments with product and research goals
Full Job 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. 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. - Build the Future of Declarative Data Pipelines 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. ABOUT DYNAMIC TABLES Dynamic Tables (DTs) are Snowflake's declarative streaming transformation primitive. Customers define a SQL query and a freshness target; Snowflake handles the rest: orchestrating refreshes, maintaining snapshot consistency https://dl.acm.org/doi/10.1145/3722212.3724455 across a DAG of dependencies, and automatically incrementalizing https://dl.acm.org/doi/10.1145/3589776 the computation so that cost scales with what changed. Dynamic Tables is one of the fastest growing products at Snowflake and is a core part of
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