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.
Snowflake's rise as a revolutionary cloud data warehouse was fueled by a key architectural tenet: separating compute from storage through a world-class metadata engine. Now, as we transition to the “Interoperable Data + AI Cloud”, metadata and open standards are the keys to unlocking the agentic enterprise at scale.
AI agents cannot reason over raw data; they require deep context, strict governance, and instant interoperability. To usher in this new era, we are seeking AI-native systems thinkers to architect the foundational substrate that allows autonomous AI to query, understand, and act upon exabyte-scale datasets regardless of whether that data is stored directly within Snowflake or resides externally in a customer managed lakehouse.
The Mission: Interoperability and Metadata as the Engine for AI
As part of the Snowflake Interoperable Foundations organization, you will lead a 0->1 ground-up redesign of our core metadata and storage architecture.
Metadata engineering and open standards (like Apache Iceberg) are the linchpins of Snowflake's future. They are what allow us to bring Snowflake's industry-leading performance and governance to data sitting anywhere in the world. Your mission is to evolve this architecture so that open, multi-format data lakes are not just searchable by humans, but inherently AI-ready by transforming interoperable metadata into the contextual engine that powers agentic innovation.
Your Impact: Architecting the Data + AI Cloud
0->1 Metadata Redesign: Lead the ground-up re-architecture of our core metadata systems. You will build the highly concurrent transaction frameworks that power query, DML, and AI-driven data interactions, ensuring our metadata layer scales to support the massive contextual demands of agentic AI.
Championing the Open Standard (Apache Iceberg): Drive industry-defining innovations on Apache Iceberg. You will ensure open table formats are no longer just storage abstractions, but first-class citizens that deliver native-level performance and governance for analytics, data engineering, and AI workloads without vendor lock-in.
Building the Agentic Foundation: AI needs context to act safely and accurately. You will build the rich metadata structures that provide AI agents with the semantic understanding and governance required to navigate and manipulate massive global datasets.
Scale & Systems Resilience: Solve non-negotiable challenges in fault tolerance, high availability, and extreme performance for a global ecosystem that treats multi-cloud resiliency as a baseline requirement.
Strategic Influence: Own the end-to-end platform architecture, set and shape the future roadmap for how metadata interfaces with AI, and mentor the next generation of engineers in a low-ego, high-impact environment.
What You Bring:
15+ Years Systems Experience: A proven track record of designing, building, and operating large-scale distributed systems and solving difficult multi-cloud interoperability challenges.
Database Internals Builder: Deep expertise in “building” database, metadata management, query optimization, data catalog, compaction, or large-scale state management systems.
0->1 Technical Leadership: A history of implementing greenfield, cloud-scale solutions and migrating massive, high-throughput distributed systems to next-generation architectures.
Core Systems Fundamentals: Strong grasp of storage performance, distributed consistency trade-offs, and algorithms.
Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.
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
- 15+ years of industry experience designing, building and supporting large scale distributed services
- Deep and broad expertise in a variety of database systems internals including metadata management, clustering, compaction, catalogs, storage and replication
- Strong computer science fundamentals including data structures, algorithms, and distributed systems
- Excellent understanding of systems infrastructure product development concepts including multi-threading, memory management, networking and storage, performance, reliability and scalability
- Fluency in Java or other similar procedural object-oriented language
- BS in Computer Science; Advanced degree preferred
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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Fair & Transparent Compensation — Pay is widely viewed as competitive and aligned with market value, with “fair pay” and top-tier total compensation frequently cited for engineering and technical roles.
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Equity Value & Accessibility — Equity and ESPP participation are standout components of total compensation, with robust RSU grants often highlighted as a major advantage, particularly in engineering.
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Healthcare Strength — Health coverage is described as strong and comprehensive, complemented by wellness resources and related programs.
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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