Engineering Manager, Data Engineering Experience
Snowflake is hiring an Engineering Manager, Data Engineering Experience for a remote role open to applicants in United States. It pays $236k-$339k a year and Level rates it ; you can apply on Snowflake.
Level's read on this job
- Level rates this data engineer role Little AI ●○○○: aI is not part of the work.
- Pay on this posting starts 57% higher than the typical data engineer posting on Level.
- This is listed as a remote role.
- The posting mentions Databricks, React and TypeScript among its tools and skills.
- Snowflake has 354 other open roles on Level.
AI in this role
Lead an engineering team building developer experiences and data engineering workloads for Snowflake's data platform.
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.
Team Scope
You'll lead a team of 10 engineers owning the Developer Experience for authoring data engineering workloads, reporting to the manager who oversees DEX across all geographies. Every place a data engineer writes, runs, automates, or debugs their work is something we build, shape, or contribute to:
Workspaces — the primary browser-based, multi-file IDE in Snowsight. Full-stack: a React/TypeScript front end on top of our own backend platform. We are the single largest contributor to this surface in net-new feature capabilities.
Cortex Code Desktop — the local, VS Code-grade development experience for building on Snowflake (CoCo). We develop DE-focused experiences inside of the Desktop editor as first-class experiences.
Cortex Code CLI — the command-line developer experience for the same workflows, for engineers who live in the terminal. We develop skills that go out to customers, as well as frameworks and technologies internally to build and test the agent and skills more rapidly.
Pipeline Observability UIs — the in-product monitoring surfaces for deployed pipeline objects in Snowflake
The products you'll ship on those surfaces
dbt Projects on Snowflake (GA) — build, run, schedule, and monitor dbt natively inside Snowflake, no external orchestrator.
DCM (Database Change Management, Public Preview) — declarative, git-integrated infrastructure-as-code for Snowflake objects. Customer asks were blunt: "get rid of Terraform." DCM is the deployment backbone under both Pipeline Builder and dbt Projects.
Pipeline Builder (private preview, heading to public preview) — a visual, drag-and-drop orchestration canvas that compiles to DCM and deploys as a task graph. This is our answer to Databricks' Lakeflow Designer and Airflow. One of the biggest Snowflake launches coming this summer.
More to come! This is a team with a track record of shipping fast, and there's plenty more on the roadmap.
What we're looking for
3-5 years of management experience
A track record of leading technical teams, plus experience with modern IDEs, distributed build systems, and cloud-based dev environments.
Strong Product Instincts — Able to confidently meet with customers (internal, external, product mgr hat), understand their problems, have a deep understanding of the existing product, and use that knowledge to author roadmaps, create project plans, and suggest novel product solutions.
Excellent Cross Functional Relationship Building – DEX touches all parts of Snowflake’s software stack, with deliverables from UX down to bare metal. Building relationships and managing expectations is critical to making the whole of the product greater than the sum of its parts.
Hands-on Experience – Build real projects to test the product, find the hard edges, make fixes, and develop opinions. Become an advocate for your own products and how to take them to the next level. Use AI extensively to empower your decision making.
Passion mentoring and being mentored – Snowflake has a strong culture for growing people. We invest in others and ourselves. Having examples where you’ve concretely impacted those around you is critical.
Bonus: dbt, Airflow, Spark, or similar experience with Data Engineering frameworks/tools
Authoring is the front door. Everything a data engineer does on Snowflake starts on one of our surfaces — so the experience here directly drives DE adoption and consumption.
Agentic authoring is our FY27 big bet. Natural-language pipeline authoring in our products is a leapfrog opportunity over the competition and we demoed a lot of this at Summit
A four-year roadmap is ready to converge into one, cohesive product. Workspaces, DCM, Cortex Code, Pipeline Builder, and their underlying primitives are coming together into one coherent authoring story, and this role is stitching them together.
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
Engineering Manager, Data Engineering Experience at Snowflake rates 25 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ 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.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- This job starts at
- $236k
- Typical data engineer job
- $150k
This posting starts 57% above the typical data engineer job. See data engineer jobs
Questions you could be asked
- Tell me about a project where engineering management was part of your work. What did you do?
- Tell me about a project where developer experience was part of your work. What did you do?
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Walk me through how you've used Databricks in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Engineering Management, Developer Experience, Data Engineering, Distributed Systems, and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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