Engineering Manager/Tech Lead Manager - Runtime Engineering

About this role

Snowflake

Engineering Manager/Tech Lead Manager - Runtime Engineering

US-CA-Menlo Park +1Full-timeLead & above

Checked 1d ago

Posted 22 Oct 2026 on Snowflake's careers page

What the interview will test

Engineering Manager interviews are usually assessed on

• Leadership & Influence
• Stakeholder Communication
• Prioritization & Trade-offs
• Conflict Resolution
• Talent Assessment & Hiring
• Execution & Roadmapping

Practicing for this role builds your session around these skills, with this posting's own requirements folded in.

What you'd do

• 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.
• Own the production quality of the team’s components, including observability, incident response, fault recovery, and safe rollout practices.
• Hire, coach, and develop engineers; provide actionable feedback, manage performance, and support career growth across experience levels.
• Partner with senior technical leaders and Product Management to prioritize investments, manage dependencies, and deliver a realistic roadmap.
• Validate changes against representative customer workloads and track measurable improvements in compatibility, latency, reliability, and cost-efficiency.

What they're looking for

• 2+ years of direct engineering management experience, with demonstrated success developing engineers and delivering production systems.
• 5+ years of hands-on software engineering experience, including substantial work on compilers, query-processing systems, or runtime infrastructure.
• Deep expertise in at least one relevant area, such as compiler architecture and IR 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 review production code and guide technical decisions.
• 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 engineering priorities and collaborate effectively across teams and locations.

Nice to have

• 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 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.

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