S

Snowflake

Runs a cloud platform for business data and AI

Staff Software Engineer - Compiler & Spark Runtime

Systems Software EngineeringPosted on Nov 13
Full-time$236k - $339.2k /yrHybrid

About the Job

Requirements

  • At least 10 years of hands-on software engineering experience, including substantial work on compilers, query-processing systems, or runtime infrastructure.
  • Experience serving as a technical lead for complex engineering initiatives, guiding engineers and coordinating delivery without requiring formal management authority.
  • A track record of designing, implementing, and delivering production systems, with ownership of significant architectural and implementation decisions.
  • Deep expertise in at least one relevant area, such as compiler architecture and intermediate-representation transformations, relational query processing, language semantics and type systems, or runtime integration.
  • Proficiency in Scala, Java, C++, or a comparable implementation language, with the ability to write and review production code.
  • Strong systems fundamentals, including concurrency, memory behavior, and performance analysis, together with experience debugging complex production issues.
  • Ability to translate technical and customer requirements into practical engineering priorities and collaborate effectively across teams and locations.
  • Strong technical communication and mentorship skills, including the ability to build alignment around architectural decisions and explain complex trade-offs.

Responsibilities

  • Lead the technical design and implementation of Spark query compilation and runtime integration, including intermediate representations, type resolution, semantic compatibility, query-plan transformations, and efficient SQL generation.
  • Own complex engineering initiatives from problem definition and architecture through implementation, validation, and production rollout.
  • Provide technical leadership to project teams by clarifying engineering trade-offs, aligning contributors, reviewing designs and code, and resolving technical blockers.
  • Improve end-to-end workload performance and cost-efficiency through profiling, compilation-latency reduction, metadata-access improvements, and collaboration with query-engine teams.
  • Establish correctness and compatibility practices, including differential testing against Apache Spark, regression coverage, and clear handling of unsupported behavior.
  • Drive production quality for owned components, including observability, incident investigation, fault recovery, and safe rollout practices.
  • Mentor engineers through design discussions, code reviews, debugging, and knowledge sharing, strengthening the team’s technical capabilities.
  • Partner with senior technical leaders and Product Management to prioritize investments, identify dependencies, and scope deliverable engineering milestones.
  • Validate changes against representative customer workloads and track measurable improvements in compatibility, latency, reliability, and cost-efficiency.

Desired Qualifications

  • Experience with Apache Spark internals, Catalyst, Spark Connect, or DataFrame APIs.
  • Experience with relational algebra, SQL generation, query optimization, or database execution systems.
  • Experience with Scala/JVM performance, native runtime functions, metadata caching, or compilation-performance optimization.
  • Experience building compatibility-test frameworks, differential testing, performance benchmarks, or production observability for data systems.
  • Experience technically leading systems through customer adoption, production hardening, and staged releases.
  • A degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.

About the Company

Snowflake

Runs a cloud platform for business data and AI

Snowflake runs a cloud platform where businesses store and analyze data, build AI tools, and share information under common access controls. Its platform separates stored data from computing resources, letting teams run different workloads without maintaining database servers. Analysts query business records with SQL, while developers use Python and other languages to build applications and train models against the same data; Cortex connects AI models to company records so teams build assistants and automate analysis. Customers pay for storage and computing usage across Amazon, Microsoft, and Google infrastructure. Snowflake was founded in 2012 and has its headquarters in Menlo Park, California.

Company size
10,001+
Company stage
IPO
Headquarters
Menlo Park, CA
Founded
2012

Recently Posted Jobs

Explore more opportunities at Snowflake

See more jobs