Staff Software Engineer

Snowflake4 days ago

Location

US-CA-Menlo Park

Type

Full Time

Salary

USD 236,000 – 339,250

Level

Staff

Role

Staff Engineer

Posted

Jun 25, 2026

Full TimeStaff

The role

Summary

Join Snowflake's Database Engineering team as a Staff Software Engineer to architect and optimize petabyte-scale cloud data systems. This role requires deep expertise in distributed systems, query optimization, and large-scale data processing, with a focus on designing novel algorithms and service architectures that power the next generation of the Snowflake Data Cloud. Ideal candidates bring 10+ years of software engineering experience, strong proficiency in Java or C++, and demonstrated mastery of database internals, distributed systems concepts, and systems programming at enterprise scale.

What you'll do

Design and Implement Query Optimization Algorithms: Architect novel query optimization and distributed data processing algorithms to maintain Snowflake's competitive advantage in cloud data warehousing. Develop sophisticated optimization techniques that reduce query execution time and resource consumption across petabyte-scale datasets while maintaining query accuracy and consistency.

Build Petabyte-Scale Database Systems: Design, develop, and support highly parallel, fault-tolerant cloud database systems capable of processing massive datasets. Engineer systems with built-in resilience, automatic failover mechanisms, and self-healing capabilities to ensure production reliability at enterprise scale.

Develop Next-Generation Service Architecture: Lead the design and implementation of new service architecture patterns required for the next generation of the Snowflake Data Cloud. Define microservices boundaries, inter-service communication protocols, and deployment strategies that enable scalability, maintainability, and rapid iteration.

Diagnose and Resolve Performance Bottlenecks: Analyze system performance metrics, identify scalability constraints, and implement targeted optimizations. Profile complex distributed systems to pinpoint bottlenecks in CPU, memory, I/O, and network layers, then design and execute solutions that maintain or improve system efficiency.

Own End-to-End Project Delivery: Take full ownership of projects from requirements gathering through production deployment. Develop comprehensive design documents, implement robust solutions, execute rigorous testing protocols including performance and chaos engineering tests, and manage safe rollouts with monitoring and rollback strategies.

Ensure Production Operational Excellence: Execute production operations and on-call responsibilities for critical systems, ensuring strict adherence to SLAs for durability, availability, and performance. Develop runbooks, monitoring dashboards, and alerting systems that enable rapid incident response and maintain customer trust.

Build Reliable Enterprise-Grade Software: Develop high-quality, highly reliable software architecture and implementations that meet the rigorous demands of the world's largest enterprises. Apply defensive programming practices, comprehensive testing strategies, and code review discipline to minimize defects and security vulnerabilities.

Develop Customer Insight Tools: Create tools and interfaces that provide customers with deep visibility into their workload behavior, query performance, resource utilization, and system health. Design user-friendly dashboards and diagnostic tools that empower customers to optimize their database usage patterns.

Evangelize Database Best Practices: Share technical expertise across the organization and with customers regarding optimal database architecture patterns, query design principles, and system configuration strategies. Contribute to technical documentation, blog posts, and conference presentations that establish Snowflake's thought leadership.

Mentor and Develop Engineering Talent: Guide and support the professional growth of junior engineers on the Database Engineering team. Conduct code reviews, provide technical mentorship, delegate challenging projects for skill development, and contribute to team knowledge sharing and engineering excellence culture.

What we look for

Technical

Distributed Systems ArchitectureDeep understanding of distributed systems concepts including consensus algorithms, consistency models (strong, eventual, causal), fault tolerance mechanisms, leader election, and recovery protocols. Experience designing systems that maintain correctness and performance across multiple nodes with partial failure scenarios.

Systems Programming and ConcurrencyAdvanced proficiency in multi-threaded and concurrent programming patterns including lock-free algorithms, mutex management, memory ordering, and deadlock prevention. Understanding of operating system primitives, thread scheduling, and performance implications of synchronization strategies.

Java or C++ MasteryStrong fluency in either Java or C++ with demonstrated ability to write performant, maintainable code at scale. For C++: memory management, template metaprogramming, performance optimization; For Java: generics, lambda expressions, garbage collection tuning, and framework mastery.

Computer Science FundamentalsSolid foundation in core CS concepts including advanced data structures (B-trees, hash tables, skip lists), algorithm analysis and Big O complexity, dynamic programming, graph algorithms, and their practical applications in database and distributed systems contexts.

Linux Development EnvironmentPractical experience with Linux kernel concepts, system calls, shell scripting, and development tools. Proficiency with performance profiling tools (perf, strace), debugging utilities (gdb, valgrind), and version control systems. Comfortable with containerization technologies and deployment environments.

Implementation, Testing, and DebuggingExperience with comprehensive testing strategies including unit testing, integration testing, performance testing, and chaos engineering. Proficiency in debugging complex systems using debuggers, logging frameworks, and instrumentation. Strong documentation practices for code and architecture.

Education

Bachelor's Degree in Computer Science or Related FieldBachelor's degree or equivalent in Computer Science, Software Engineering, Computer Engineering, or related discipline. Formal education should demonstrate strong foundation in algorithms, data structures, systems theory, and software engineering principles.

Experience

10+ Years Commercial or Open-Source Software DevelopmentMinimum 10 years of professional experience building commercial or open-source software systems. Demonstrated progression through increasingly complex technical challenges, with proven ability to architect and deliver production systems serving large user bases or handling significant scale.

Large-Scale Distributed Systems ExperienceSubstantial experience designing, implementing, or maintaining distributed systems handling petabyte-scale data or high-throughput transaction processing. Understanding of operational challenges, monitoring requirements, and disaster recovery procedures for mission-critical infrastructure.

Performance Optimization and ProfilingTrack record of identifying and resolving performance bottlenecks in complex systems. Experience with benchmarking methodologies, performance regression detection, and optimization techniques across multiple system layers (algorithm, data structure, OS, hardware level).

Skills

Required skills

Java ProgrammingProduction-level proficiency in Java for building large-scale systems. Experience with Java concurrency libraries, performance tuning, garbage collection optimization, and modern Java features.

C++ ProgrammingProduction-level proficiency in C++ for systems programming. Experience with memory management, template programming, and high-performance code optimization.

Distributed Systems DesignAbility to architect systems with distributed consensus, fault tolerance, and consistency guarantees. Understanding of consensus protocols, data replication, and failure recovery mechanisms.

Database Systems KnowledgeUnderstanding of relational database concepts, transaction processing, ACID properties, and query execution fundamentals. Experience working with or building database systems, even if not as primary responsibility.

Data Structures and AlgorithmsExpert-level knowledge of advanced data structures (trees, hash tables, graphs) and algorithm design. Ability to analyze complexity and select optimal approaches for technical problems.

Nice to have

SQL and Database InternalsDeep knowledge of SQL semantics, query planning, and execution engines. Experience with database optimization including indexing strategies, query rewriting, and cost-based optimization techniques.

Query Optimization and Compiler DesignExperience with query optimization algorithms, query parsing, semantic analysis, and compilation techniques. Understanding of cost models, heuristic optimization, and plan generation strategies.

Distributed Key-Value Store InternalsFamiliarity with internals of systems like FoundationDB, Memcached, or Redis. Experience understanding how these systems implement consistency guarantees, replication, and fault tolerance.

Storage Engine ArchitectureKnowledge of storage engine implementations such as RocksDB, InnoDB, BerkeleyDB, or LSM trees. Understanding of write optimization, compression techniques, and persistent storage strategies.

MySQL and PostgreSQL InternalsDeep understanding of MySQL or PostgreSQL architecture including buffer management, transaction processing, replication mechanisms, and query optimization techniques used in production databases.

Data Warehouse and AnalyticsExperience with data warehouse design patterns, columnar storage formats, analytical query patterns, and large-scale data processing frameworks like Apache Hadoop and Spark.

Database Replication TechnologyExperience implementing or working with database replication systems including master-slave replication, multi-master architectures, and maintaining consistency across replicas during failures.

Big Data Storage TechnologiesKnowledge of distributed storage systems including HDFS, Cassandra, HBase, columnar databases, and other technologies designed for petabyte-scale data storage and retrieval.