Senior Fullstack Engineer

Snowflake2 days ago

Location

US-CA-Menlo Park

Type

Full Time

Salary

USD 200,000 – 287,500

Level

Senior

Role

Full Stack Engineer

Posted

Jul 7, 2026

Full TimeSenior

The role

Summary

Join Snowflake as a Senior Fullstack Engineer to architect and ship AI-native business intelligence experiences. You'll lead end-to-end development of lightweight, scalable analytics capabilities across React, Go, and Java, combining startup velocity with enterprise-grade system design. This role offers the opportunity to redefine enterprise analytics in the agentic AI era, working closely with product and design teams to deliver customer-facing features that empower business users to transform raw data into actionable insights.

What you'll do

Full-Stack Product Development: Design, architect, and implement core product capabilities for AI-native dashboards and analytics experiences across the entire stack, leveraging React for responsive user interfaces, Go for high-performance backend services, and Java for robust enterprise systems.

End-to-End Project Leadership: Own projects from conception through delivery, making critical architectural decisions and product tradeoffs across frontend user experience, backend scalability, data pipeline optimization, and cross-platform consistency while maintaining code quality standards.

Cross-Functional Collaboration: Partner seamlessly with product managers, design teams, and sister engineering teams to gather requirements, iterate on prototypes, and deliver cohesive user experiences that balance business objectives with technical feasibility.

System Design & Architecture: Build robust, scalable systems capable of handling enterprise-scale data workloads and concurrent user sessions, implementing patterns for maintainability, fault tolerance, and performance optimization in complex distributed environments.

Technical Mentorship & Culture: Mentor junior and mid-level engineers, conduct technical code reviews, establish engineering best practices, and help shape technical direction through architectural guidance and decision-making frameworks.

AI-Augmented Development: Leverage modern AI tools and large language models to accelerate development cycles, improve code quality, and rapidly prototype features, treating AI as a high-trust collaborator in the development process.

What we look for

Technical

Full-Stack JavaScript/React ExpertiseStrong proficiency with React and modern JavaScript/TypeScript, including component architecture, state management (Redux, Context API), performance optimization, and building responsive, accessible user interfaces for analytical applications.

Backend System DesignProduction experience building scalable backend services with Go or Java, including REST/GraphQL API design, database optimization, caching strategies, asynchronous processing, and handling high-concurrency scenarios.

Database ArchitectureSolid understanding of relational databases (SQL), distributed query optimization, data warehousing concepts, and ability to work effectively with cloud-based data platforms like Snowflake's data warehouse infrastructure.

Cloud InfrastructureHands-on experience with cloud platforms (AWS, GCP, or Azure), containerization (Docker/Kubernetes), CI/CD pipelines, and deploying scalable microservices in production environments.

Software Architecture PatternsDeep knowledge of enterprise architecture patterns, microservices design, system decomposition, API design, and ability to make technical tradeoffs between speed, quality, and long-term maintainability.

AI/ML IntegrationDemonstrated ability to integrate and leverage modern AI tools (LLMs, generative AI frameworks) into development workflows and product features, with understanding of AI-augmented user experiences.

Education

Bachelor's Degree in Computer Science or Related FieldFormal education in Computer Science, Software Engineering, or equivalent field providing foundational knowledge in algorithms, data structures, systems design, and software engineering principles.

Experience

5+ Years Full-Stack Engineering ExperienceProven track record shipping customer-facing products at scale, with significant hands-on experience across frontend, backend, and infrastructure across multiple product cycles.

3+ Years Senior-Level EngineeringDemonstrated impact at senior level including project ownership, technical mentorship, architectural decision-making, and influence on engineering culture and direction.

Enterprise-Scale System DevelopmentExperience designing and building robust systems handling millions of transactions, complex data pipelines, or high-concurrency scenarios with performance, reliability, and security requirements.

Product-Oriented DevelopmentTrack record of making product decisions informed by user feedback, business context, and technical constraints, with ability to influence product direction and advocate for users' needs.

Skills

Required skills

ReactExpert-level proficiency with React including hooks, component composition, performance optimization, and building complex interactive user interfaces for data analytics and dashboards.

TypeScript/JavaScriptStrong command of modern JavaScript and TypeScript for building type-safe, maintainable frontend applications with ES6+ features and modern tooling.

GoProduction experience developing backend services in Go with understanding of goroutines, channels, interfaces, and building concurrent, high-performance network services.

JavaProficiency in Java for enterprise backend services, including Spring/Spring Boot frameworks, dependency injection, and building scalable microservices.

System DesignAbility to architect scalable systems, design APIs, implement caching strategies, optimize database queries, and make informed decisions about technology choices.

SQL & Data QueryingFluency with SQL for complex queries, query optimization, understanding of database indexing, and working with cloud data warehouses.

Full-Stack Problem SolvingAbility to debug and optimize performance across the entire stack, from frontend rendering to database query execution.

AI Tool ProficiencyHighly fluent with modern AI assistants and code generation tools (ChatGPT, Copilot, Claude) for accelerating development, code review, and problem-solving.

Nice to have

Analytics & BI Product ExperiencePrior experience building business intelligence, analytics, or data visualization tools, with understanding of BI tool architecture and analytical query patterns.

Data Warehouse ExpertiseFamiliarity with Snowflake's platform, cloud data warehousing concepts, or experience optimizing queries against large analytical datasets.

GraphQLExperience building and consuming GraphQL APIs as an alternative to REST, providing efficient data fetching for client applications.

AI/ML IntegrationExperience integrating LLMs, generative AI models, or AI-augmented features into production applications, including prompt engineering and AI workflow optimization.

Advanced Algorithm KnowledgeFamiliarity with the Yegge Scale or equivalent advanced algorithmic thinking, demonstrating capability to solve complex computational problems.

Distributed SystemsUnderstanding of distributed computing concepts, consistency models, fault tolerance, and experience with scalable architectures handling millions of concurrent users.

Performance EngineeringProven ability to profile applications, identify bottlenecks, and implement optimizations across frontend rendering, API response times, and query execution.

Compensation & benefits

Salary

USD 200,000 – 287,500 (annual)

Stock options

Available

Benefits

Competitive Equity & Stock Options

Participate in Snowflake's success through stock options and equity grants, with potential for significant upside as the company continues its growth trajectory in AI-native enterprise platforms.

Comprehensive Health & Wellness

Medical, dental, and vision insurance coverage plus mental health resources, wellness programs, and fitness benefits supporting overall employee wellbeing.

Retirement Planning

401(k) retirement savings plan with employer matching contributions, helping build long-term financial security.

Professional Development

Learning budgets, technical conference attendance, internal training programs, and mentorship opportunities to advance skills in emerging technologies like AI/ML systems.

Flexible Work Environment

Flexible work arrangements supporting remote and hybrid work options, allowing work-life balance while maintaining strong team collaboration.

Generous PTO & Leave

Competitive paid time off, parental leave, sabbatical options, and time for personal wellbeing and family needs.

Innovation Opportunities

Exposure to cutting-edge AI, data warehousing, and analytics technologies, working on products at the forefront of enterprise innovation.

Inclusive Culture

Commitment to diversity, equity, and inclusion with employee resource groups, sponsorship programs, and supportive community within a rapidly growing organization.

Interview process

1
Initial Screening Call — 30-minute conversation with recruiter to assess background, motivation, and alignment with role requirements. Prepare to discuss specific full-stack projects you've owned and your experience with AI-augmented development.
2
Technical Phone Screen — 45-60 minute conversation with an engineer covering system design, architecture decision-making, and technical depth across frontend and backend. Be ready to discuss tradeoffs between React optimization strategies and backend scalability patterns.
3
System Design Interview — 60-90 minute technical interview focused on designing scalable systems for analytics use cases. Expect questions around distributed system architecture, query optimization for data warehouses, and building user-facing analytics products at enterprise scale.
4
Frontend Technical Assessment — Coding exercise or project focused on React component development, state management, and building interactive UI for analytical visualizations. May involve building dashboard components with real-time data updates.
5
Backend Technical Assessment — Coding challenge focused on Go or Java backend system design, focusing on API design, database optimization, and building concurrent services. Expected to demonstrate understanding of production-grade architectural patterns.
6
Product Sense Discussion — Conversation with product manager or senior engineer about your approach to building product features, making tradeoffs, and user experience considerations specific to analytics and BI tools.
7
Full-Stack Project Walkthrough — Deep dive into a significant project you've shipped, discussing architectural decisions, technical tradeoffs, how you collaborated across teams, and lessons learned in complex full-stack environments.
8
Mentorship & Culture Fit — Conversation with a senior engineer or engineering manager exploring your approach to mentoring others, raising engineering standards, and contributing to team culture and technical direction.