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.
About the Team
The Data Engineering Team builds the foundational infrastructure that powers our organization’s data ecosystem. However, our platform’s true value is realized when it is successfully integrated and operationalized within our customers' environments.
The Forward Deployed Engineering (FDE) group is the elite, customer-facing engineering arm of our Data Engineering team. FDEs bridge the gap between our core product and the complex, real-world data environments of our enterprise customers. You will build and deploy directly within our customers' diverse, highly secure ecosystems—leveraging the Snowflake AI Data Cloud to turn platform capabilities into production-ready data applications, workflows, and agentic AI solutions that solve critical business challenges.
The Role
As a Forward Deployed Engineer, you are a full-stack data practitioner who owns the actual code, configuration, optimization, and production deployment inside the customer's ecosystem.
You will dive deep into ambiguous data environments, navigate complex enterprise security controls, and rapidly prototype and deploy robust, production-grade solutions natively on top of Snowflake. Your mission is to minimize time-to-value for the customer, ensuring our platform integrates flawlessly with their existing pipelines, identity providers, and data governance frameworks.
When you complete an engagement, you don't just leave the customer with a slide deck; you leave them with a fully operational, production-hardened system running smoothly on their Snowflake stack.
What You Will Do
Execute In-Environment Deployments: Partner directly with customer technical teams to design, build, and deploy production-grade data pipelines, analytics tools, and automated workflows natively within their Snowflake environments.
Build Advanced Snowflake Pipelines: Develop and maintain high-performance, cost-effective data workloads utilizing Snowpark (Python/SQL), Dynamic Tables, Streams, and Tasks.
Deploy Native AI & Agentic Workflows: Integrate advanced platform capabilities directly into customer environments using Snowflake Cortex AI (Cortex Search, Cortex Analyst, and LLM functions) to safely orchestrate intelligent workflows on top of the customer's proprietary data.
Solve Security & Governance Hurdles: Implement secure data ingestion and egress patterns that comply with strict customer data governance, masking policies, zero-trust networking, and compliance requirements.
Drive Cross-Functional Synergy: Collaborate intensively with Product, Sales Engineering, and Customer Success stakeholders. You will synchronize on strategic customer priorities, proactively identify and mitigate technical blockers, and orchestrate friction-less operational transitions following production deployment.
Rapid Prototyping & Custom App Building: Translate complex, highly ambiguous customer business requirements into working technical solutions. Build lightweight front-end data applications (e.g., via Streamlit in Snowflake, React aaps ) to make data immediately actionable for end users.
Engineer the Core Feedback Loop: Act as the ultimate boots-on-the-ground user. Distill messy, real-world customer deployment challenges and product friction points into structured, actionable feedback to help our core engineering team improve the data platform.
Technical Enablement: Document bespoke deployment architectures and runbooks. Train and mentor customer data teams to ensure they can confidently operate, optimize, and scale the systems you build.
Who You Are (Requirements)
Customer-Facing Engineering Grit: You love working directly with customers, mapping out their technical pain points, and writing the code that solves them. You are comfortable being the technical face of the platform.
Expert Software & Data Engineering Skills: * Strong proficiency in Snowflake ,Python (modern, clean, production-grade) to build data applications, automation scripts, and Snowpark procedures.
Deep Snowflake Ecosystem Knowledge: 4+ years of hands-on experience architectural design and implementation within the Snowflake AI Data Cloud, including experience with Snowsight, data shares, and compute warehouse tuning.
Experience with Enterprise Data Stacks: Hands-on experience working with modern cloud data infrastructure (AWS, Azure, or GCP), ETL/ELT orchestration tools (e.g., dbt, Airflow), and enterprise security frameworks (IAM, VPCs, Private Link).
Thrives in Customer Ambiguity: You are comfortable walking into a customer environment with minimal documentation, uncovering how their data flows, and determining the fastest path to production.
Bonus Points If You Have...
Prior experience as an FDE at a high-growth data, AI in snowflake
Hands-on experience building custom web/data apps integrated with enterprise identity providers (OIDC, SAML).
Willingness to travel (up to 25%) to collaborate onsite with strategic enterprise customers.
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