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.
As a Principal Engineer on the Data Platform team, you will be a technical anchor — setting direction, solving the hardest engineering problems, and elevating the entire team. You will work at the intersection of systems design, long-term architecture, and real-world engineering execution. In this specific role, you will lead the evolution of our declarative data pipelines, focusing on streaming ingestion and transformations.
What You'll DoDrive the technical strategy and architecture for key Data Platform initiatives, focusing heavily on real-time data movement and incremental processing.
Lead design reviews and set engineering standards across teams.
Identify and resolve high-impact technical challenges and systemic bottlenecks to reduce latency and improve the efficiency of dynamic tables at cloud scale.
Mentor and grow senior engineers; raise the engineering bar.
Partner closely with product and infrastructure leadership on roadmap and direction.
Continuous hands-on technical deliverables in the most critical areas.
14+ years of software engineering experience with deep expertise in distributed systems.
Demonstrated track record of defining and delivering platform-scale technical initiatives.
Expert-level knowledge of streaming and/or batch data systems (Flink, Spark, or equivalent), with specialized knowledge in incremental materialization algorithms.
Strong systems thinking — ability to reason across layers of complexity (infra, storage, compute, API).
A passion for engaging directly with customers to gain insight and inspiration
Experience influencing technical direction across organizations
Excellent written and verbal communication for technical and executive audiences.
Experience with AI-augmented development practices and integrating LLM-based tooling into engineering workflows.
Familiarity with Snowflake platform internals or cloud-native data systems.
Experience with metadata systems, query optimization, or data catalog infrastructure.
Contributions to open source, such as top-level Apache projects
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
Skills Required
- 14+ years of software engineering experience with deep expertise in distributed systems.
- Demonstrated track record of defining and delivering platform-scale technical initiatives.
- Expert-level knowledge of streaming and/or batch data systems (Flink, Spark, or equivalent) with specialized knowledge in incremental materialization algorithms.
- Strong systems thinking and ability to reason across infra, storage, compute, and API layers.
- Experience engaging directly with customers to gain insight and inspiration.
- Experience influencing technical direction across organizations.
- Excellent written and verbal communication for technical and executive audiences.
- Experience with AI-augmented development practices and integrating LLM-based tooling into engineering workflows.
- Familiarity with Snowflake platform internals or cloud-native data systems.
- Experience with metadata systems, query optimization, or data catalog infrastructure.
- Contributions to open source, such as top-level Apache projects.
Snowflake Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Snowflake and has not been reviewed or approved by Snowflake.
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Equity Value & Accessibility — Equity grants (RSUs) and an ESPP are central to total compensation and are described as highly valuable. Feedback suggests many see equity as a major satisfaction driver with meaningful upside potential.
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Fair & Transparent Compensation — Pay is considered competitive and accompanied by clear communication on salary, equity, and advancement. Feedback suggests pay practices emphasize fairness and transparency.
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Parental & Family Support — Paid parental leave, fertility benefits, adoption assistance, and family planning resources are notably comprehensive. Feedback suggests these programs materially support major life events.
Snowflake Insights
What We Do
Snowflake powers the end-to-end data lifecycle – from ingesting and processing data to analyzing and modeling it, to building and sharing data and AI applications – helping engineers, analysts, and leaders innovate faster and achieve more with their data. We're on a mission to empower every enterprise to achieve its full potential through data and AI.
Why Work With Us
Snowflake is where data does more, and so do you. More innovating, more growing, and more collaborating. Here, you’ll find the sweet spot between building big and moving fast, in technology and your career.
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