Engineering Manager/Tech Lead Manager - Runtime Engineering

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.

ENGINEERING MANAGER – SPARK RUNTIME ENGINEERING

Location: Bellevue, WA or Menlo Park, CA

ABOUT THE TEAM

The Spark Runtime Engineering Team brings Snowflake’s performance, efficiency, and reliability to Spark workloads. Our mission is to help customers scale data processing while preserving the familiar Spark APIs and semantics they rely on. We build the compiler and runtime integration that translate Spark workloads into efficient execution on Snowflake’s cloud-native query engine. This includes tackling complex challenges in compiler infrastructure, query-plan lowering, Spark compatibility, execution integration, and end-to-end observability to deliver faster, more cost-efficient data processing at scale.

We are seeking a hands-on Engineering Manager who combines deep technical expertise with strong people leadership. You will shape the team’s technical direction, stay actively engaged in architecture and critical engineering decisions, and hire, mentor, and grow a high-performing engineering team to advance the future of Spark on Snowflake.

ROLE OVERVIEW

You will lead a team of approximately 5–8 engineers building production compiler and runtime capabilities for Spark workloads on Snowflake. You will guide architectural decisions, review critical designs and code, and help investigate complex correctness, performance, and reliability issues. In partnership with compiler, query engine, runtime, and product teams, you will turn customer needs into a focused roadmap and measurable engineering outcomes.

RESPONSIBILITIES

- Set technical direction for Spark query compilation and runtime integration, including intermediate representations, type resolution, semantic compatibility, query-plan transformations, and efficient SQL generation.

- Improve end-to-end workload performance and cost-efficiency through profiling, compilation-latency reduction, metadata-access improvements, and collaboration with query-engine teams.

- Establish strong correctness and compatibility practices, including differential testing against Apache Spark, regression coverage, and clear handling of unsupported behavior.