Cloud Support Engineer

Posted 24 Days Ago
Be an Early Applicant
Dublin, CA, USA
In-Office
96K-126K Annually
Junior
Artificial Intelligence • Big Data • Cloud • Machine Learning • Software • Database • Analytics
Let's build a world where data and AI turn possibilities into reality.
The Role
Manages customer technical cases from triage through resolution, using AI-assisted diagnostics, SQL, logs, scripting, and troubleshooting across Snowflake and cloud environments. Communicates with customers, owns incidents, documents solutions, reports bugs, collaborates with Engineering and Product, and improves knowledge bases and support workflows. Provides coverage through weekend, holiday, and on-call rotations while troubleshooting MLOps pipelines, model performance, APIs, and infrastructure.
Summary Generated by Built In

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.

Cloud Support Engineer (CSE)

Snowflake seeks early-career Cloud Support Engineers who combine technical expertise, customer empathy, and an AI-first mindset. Fluency in Japanese (spoken and written) and familiarity with Japanese business culture; experience living or working in Japan preferred. You'll leverage and refine AI tools to accelerate troubleshooting, improve knowledge bases, and reduce time to resolution—safely and responsibly. Experience in 24x7 technical support, escalation handling, on-call rotations, and incident management is ideal.

 

Key Responsibilities:

As a Cloud Support Engineer, you manage customer cases and are accountable for accelerating their time-to-resolution, ensuring platform stability, and driving a world-class support experience. Operating as a full-stack technical support resource, this role blends deep hands-on troubleshooting with the customer empathy and communication skills of a trusted advisor.

Customer Value and Incident Ownership

  • Own the Customer Experience: Manage customer issues from initial triage through resolution and follow-up, ensuring clear communication and timely updates.

  • Deliver Support Value with AI: Leverage AI assistants and diagnostics to accelerate triage and root-cause analysis while maintaining accuracy and safety standards.

  • Outcome-Based Support: Focus on business impact, ensuring resolutions fix issues, reduce recurrence, and improve reliability.

  • Customer Empathy and Communication: Provide technical analysis and guidance via email, web, and phone, adapting to customer expertise levels.

Technical Execution and Collaboration

  • AI-Assisted Triage: Use AI to summarize logs, generate hypotheses, and draft responses—critically validating outputs before sharing.

  • Tooling Expertise: Utilize Snowflake environment, connectors, and internal tools to investigate and test solutions.

  • Cross-Functional Collaboration: Partner with Engineering, Product, and Customer Success to resolve systemic issues.

  • Knowledge Management: Document solutions in knowledge bases, refining AI-assisted drafts for quality.

  • Feedback and Innovation: Provide input on product behavior, documentation gaps, and AI-tool performance.

  • Bug Reporting: Document and collaborate on bugs and feature requests with engineering teams.

  • Operational Coverage: Support holiday/weekend rotations and on-call requirements

Required Qualifications:

  • BS/MS in Computer Science or equivalent experience.

  • 2+ years in technical support (customer-facing, ideally 24x7).

  • Fluency in Japanese (spoken and written) and familiarity with Japanese business culture; experience living or working in Japan preferred.

  • Strong AI fluency, including prompt engineering, context management, and the ability to critically validate AI outputs and know when to fall back to manual investigation.

  • Experience with AI-powered tooling (e.g., coding assistants/agentic IDEs) and modern support environments.

  • Solid technical troubleshooting skills, including comfort with SQL, log analysis, and scripting/automation (e.g., Python, APIs, workflow tools) to diagnose issues and streamline tasks.SQL, log analysis, and scripting skills (Python, APIs).

  • Strong written/verbal English communication.

  • Basic understanding of Windows and Linux Operating Systems.

  • Basic understanding of Data Warehousing fundamentals and concepts.

  • Ability to write and understand basic SQL queries

  • Familiarity with end-to-end ML pipeline including ML modeling, feature engineering, ML model training, etc.

  • Familiarity with prompt engineering, and associated tools within the LLM ecosystem, including Langchain, vector databases, co-pilot, and open-source Hugging Face models.

  • Being able to troubleshoot and resolve issues related to MLOps pipelines, model performance, and infrastructure.

  • Familiarity with RESTful APIs and web services

Preferred:

  • Snowflake or cloud platform experience (AWS, Azure, GCP)

  • Advance Workflow automation / CI/CD tooling experience

  • AI-powered support or SRE workflow experience

  • Relevant certifications (SnowPro, cloud certs)

  • Knowledge about GPUs, CUDA, and low-level optimizations will be a plus.

  • Experience developing CI/CD components for production-ready MLOps pipelines.

  • Location: Bellevue, WA or Dublin, CA

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

  • Bachelor's or master's degree in Computer Science, or equivalent experience
  • At least 2 years of customer-facing technical support experience, ideally in a 24x7 environment
  • AI fluency, including prompt engineering, context management, and critical validation of AI outputs
  • Experience with AI-powered tooling, coding assistants, agentic IDEs, and modern support environments
  • Technical troubleshooting skills involving SQL, log analysis, Python, APIs, and workflow tools
  • Strong written and verbal English communication skills
  • Basic understanding of Windows and Linux operating systems
  • Basic understanding of data warehousing fundamentals and concepts
  • Ability to write and understand basic SQL queries
  • Familiarity with end-to-end machine learning pipelines, including modeling, feature engineering, and model training
  • Familiarity with prompt engineering and LLM ecosystem tools, including LangChain, vector databases, copilots, and Hugging Face models
  • Ability to troubleshoot MLOps pipelines, model performance, and infrastructure
  • Familiarity with RESTful APIs and web services
  • Snowflake or cloud platform experience with AWS, Azure, or GCP
  • Advanced workflow automation or CI/CD tooling experience
  • AI-powered support or SRE workflow experience
  • Relevant certifications such as SnowPro or cloud certifications
  • Knowledge of GPUs, CUDA, and low-level optimizations
  • Experience developing CI/CD components for production-ready MLOps pipelines

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.

  • 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.
  • 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.
  • Healthcare Strength — Health coverage is described as strong and comprehensive, complemented by wellness resources and related programs.

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The Company
HQ: Bozeman, MT
9,023 Employees
Year Founded: 2012

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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