Principal Software Engineer - Agentic Pipelines
Snowflake is hiring a Principal Software Engineer - Agentic Pipelines in Bellevue, United States. It pays $264k-$380k 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.
- Pay on this posting starts 57% higher than the typical software engineer posting on Level.
- The posting mentions Databricks, data engineering and distributed systems among its tools and skills.
- Level classes it as a lead role.
- Snowflake has 367 other open roles on Level.
AI in this role
Principal software engineer building core data engineering and streaming pipeline infrastructure for AI-enabled workflows.
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.
Principal Software Engineer - Agentic Pipelines
Building for AI-Enabled Data Engineers & Scientists
Data pipelines are foundational infrastructure — when they're fast, correct, and maintainable, customers build on them with confidence. If you've spent the bulk of your career building large-scale data infrastructure — designing streaming or transformation primitives, reasoning hard about consistency and fault tolerance, and owning the systems that run under millions of customer workloads — this role might be for you. You'll be working on the pipeline layer at Snowflake: the constructs that define how customers move, shape, and maintain data. AI has a real presence in this work — in how customers use these pipelines and in how we think about building them — but the core job is hard data/pipeline infrastructure engineering, and that's what we're hiring for.
About the Team
We build the core data engineering primitives that power Snowflake's streaming and transformation capabilities. From the constructs customers use to define real-time pipelines to the execution fabric that makes those pipelines reliable and cost-efficient at cloud scale, our team owns the full stack of declarative data engineering. We're a small, high-ownership team operating close to the product — which means your decisions ship, your architecture matters, and your fingerprints are on some of the most heavily used features in Snowflake's data engineering portfolio.
What You'll Do
Define and drive the technical direction for Snowflake's core data engineering and streaming transformation primitives, spanning Streams, Tasks, Dynamic Tables, and adjacent pipeline constructs.
Identify and lead multi-quarter technical investments — performance, scalability, correctness, and reliability — translating ambiguous problem spaces into concrete engineering plans with measurable outcomes.
Partner with product, research, and peer engineering teams to co-design primitives that compose cleanly across the data engineering stack.
Operate as a force multiplier: run architectural reviews, set the technical bar for design documents, and help engineers grow through high-quality feedback and sponsorship.
Work directly with customers and field teams to understand real-world usage patterns; use that signal to prioritize what matters next.
Contribute to Snowflake's technical reputation — through internal design influence, external talks, or research publications in the data engineering space.
What We're Looking For
15+ years of experience designing, building, and operating large-scale distributed data systems.
Deep expertise in at least one core area: stream processing, declarative query execution, pipeline orchestration, or data transformation at scale.
Strong computer science fundamentals — distributed systems, algorithms, fault tolerance, and consistency models.
Proficiency in C++ or Java; comfort with systems-level reasoning (latency, throughput, resource efficiency at cloud scale).
Demonstrated ability to lead cross-team technical initiatives from blank-page architecture through production at petabyte scale across thousands of concurrent workloads.
Strong written and verbal communication skills; ability to represent complex technical trade-offs clearly to engineering, product, and leadership audiences.
Nice to Have
Experience with one or more major analytical databases (Snowflake, BigQuery, Redshift, Databricks, Teradata, etc).
Hands-on background in streaming, transformation, or event-driven systems (Flink, Kafka, Spark Structured Streaming).
Familiarity with the broader data engineering ecosystem: dbt, Airflow, Fivetran, Iceberg, Delta Lake.
Experience with CDC, change propagation, or incremental computation patterns.
Advanced degree (MS or PhD) in Computer Science, with emphasis on database or distributed systems.
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
Principal Software Engineer - Agentic Pipelines at Snowflake rates 60 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.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● 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
Also common in software engineer jobs at this level
Pay
- This job starts at
- $264k
- Typical software engineer job
- $168k
This posting starts 57% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- 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?
- Tell me about a project where streaming was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
- Tell me about a project where scalability was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Engineering, Distributed Systems, Streaming, Infrastructure, and Scalability. 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.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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