Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 6 hours ago

Engineering Manager/Tech Lead Manager - Runtime Engineering

Snowflake351 open roles

Pay
$236,000 – $339,200 a year
Where
US-CA-Menlo Park
Work mode
Hybrid
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowEngineering Manager/Tech Lead Manager - Runtime EngineeringSnowflake · US-CA-Menlo Park

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Snowflake's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

11.9% of postings close within 7 days. Measured by our own scanner across the market. Snowflake postings stay open a median of 49 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.9%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 6 hours ago

Snowflake median: 49 days open

The posting

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.

- 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.

MINIMUM QUALIFICATIONS

- 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.

PREFERRED 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 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.

WHY JOIN US?

Help shape how Spark workloads run on Snowflake. You will work on technically challenging compiler and runtime problems, grow a strong engineering team, and make a measurable difference to the correctness, reliability, and cost-efficiency of customers’ data processing.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.

How do you want to make your impact?

For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com http://careers.snowflake.com

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against Snowflake's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on Snowflake's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    Snowflake's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.