Level

Snowflake

Software Engineer Manager, Data Processing

Snowflake is hiring a Software Engineer Manager, Data Processing in Zurich, Switzerland. It pays CHF 204k-CHF 293k a year and Level rates it ; you can apply on Snowflake.

Level's read on this job

  • On Level's scale, this software engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Level lists 354 other open roles at Snowflake.
  • The role was posted in the last few days.

AI in this role

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.

Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse, using open formats like Apache Iceberg, at dramatically lower cost. A dynamic Context Graph and chat-based AI SRE provide rich context and automated workflows so teams can move from detection to root cause of production issue and resolution 10x faster.

Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world's leading data platforms.

The Team

We are hiring an Engineering Manager to lead our Data Processing team in Zurich. You will start with a pizza sized team with the goal to grow further.

The team owns the core engine that makes Observe work. That includes the systems that compiles our query language OPAL into SQL, the query execution pipeline that executes user queries, the scheduler which autoscales warehouses and packs workloads for high utilization and low query latencies, and our incremental view maintenance. Building features in these systems while keeping the system healthy, cost-efficient, and resilient at petabyte scale is a constant challenge. The team sits at the heart of Observe's differentiation: a full observability platform built entirely on Snowflake.

In this role you will

  • Lead, mentor, and grow a team of backend engineers working on compiler internals, distributed scheduling, query execution, and data materialization. Coach them on their careers and help each of them reach their full potential.

  • Hire top talent, and represent Observe and Snowflake to candidates.

  • Work closely with other Observe product and backend teams to plan and execute new product features and scale existing systems to meet new challenges.

  • Work with core Snowflake engineering teams in Germany and the US to integrate Observe more deeply with Snowflake technologies. Communicate Observe's needs clearly and drive improvements in the underlying platform together.

  • Strategically reduce technical debt in the area. Know where it lives, build a plan to pay it down, and balance that plan against new feature work.

  • Keep many ongoing projects moving in parallel, setting clear priorities and making sure nothing important falls through the cracks.

  • Own the operational health of the area: performance, compute cost efficiency, on-call load, and support cost. Lead the team through production incidents and customer escalations, and drive postmortems and follow-up work.

  • Stay close to the code: write, review, and fix code when needed, and dig into real production workloads alongside the team.

Qualifications

  • Proven record managing a team of 5+ engineers that delivered complex backend or infrastructure systems in a fast-paced environment.

  • A background in database systems, such as query processing, query optimization, storage, or compilers.

  • Solid experience building and operating distributed systems.

  • Hands-on engineering skills: able to write, review, and fix production code.

  • Able to run many concurrent projects at once and to prioritize clearly between them.

  • Able to balance short-term operational needs with long-term architecture, and to make cost and performance tradeoffs based on data.

  • Experience running a team that owns production services with on-call responsibilities.

  • Excellent communicator, comfortable working across time zones and organizational boundaries.

  • A bachelor's, master's, or doctorate degree in computer science, engineering, or a related field.

Bonus Points

  • Experience with Snowflake or other large-scale data platforms or databases and knowledge of their internals.

  • Familiarity with the observability space.

  • Experience building an enterprise-grade SaaS product.

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

How we rate this

Software Engineer Manager, Data Processing at Snowflake rates 66 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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