Senior User Researcher

📍 Job Overview

Job Title: Senior User Researcher

Company: Snowflake

Location: Bellevue, Washington, United States

Job Type: FULL_TIME

Category: User Research / Product Insights

Date Posted: 2026-10-01

Experience Level: 5+ Years Industry Experience

Remote Status: Hybrid (Remote considered within the US)

🚀 Role Summary

• Drive product strategy and go-to-market decisions through expert-led qualitative and quantitative user research.

• Leverage AI as a collaborative tool to enhance research methodologies, accelerate insights generation, and improve customer outcomes.

• Partner closely with product, design, engineering, and marketing leadership to influence priorities and translate findings into actionable product improvements.

• Become a subject matter expert on customer needs, product areas, and business objectives, ensuring research directly supports strategic goals.

📝 Enhancement Note: While the role is listed as "Senior User Researcher," the emphasis on AI fluency, strategic partnership with leadership, and influencing go-to-market decisions positions this as a highly impactful, senior-level individual contributor role within a product-centric organization. The "agentic enterprise" framing suggests a forward-thinking approach to leveraging technology for enhanced productivity and decision-making.

📈 Primary Responsibilities

• Lead and execute comprehensive qualitative and quantitative user research studies, selecting appropriate methodologies to meet decision-making needs and rigor.

• Analyze and synthesize findings from user research, product usage data, and existing knowledge bases to identify critical opportunities and areas for improvement.

• Collaborate with cross-functional teams (Product, Design, Engineering, Marketing) to define research objectives, align on priorities, and ensure research insights inform strategic roadmaps.

• Translate complex customer needs and business goals into clear, actionable recommendations for product development and go-to-market strategies.

• Actively integrate AI tools and techniques into the research workflow to enhance efficiency, uncover deeper insights, and elevate the quality of research outputs.

• Champion the voice of the customer throughout the product lifecycle, advocating for user needs and ensuring customer-centricity in decision-making.

• Facilitate discussions and build consensus among stakeholders to navigate product and go-to-market tradeoffs, driving decisions through launch and adoption phases.

📝 Enhancement Note: The responsibilities emphasize a strategic partnership role, going beyond traditional research execution to actively shaping product direction and go-to-market strategy. The integration of AI is highlighted as a core competency, not just a tool.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a Bachelor's or Master's degree in Human-Computer Interaction (HCI), Psychology, Sociology, Anthropology, Computer Science, or a related field is often preferred for deep research craft. Equivalent practical experience will also be considered.

Experience: 5+ years of professional industry user research experience, with a demonstrated history of influencing product and business decisions through research.

Required Skills:

• Deep Qualitative Research Craft: Proficiency in a wide range of qualitative methods (e.g., interviews, usability testing, ethnography, diary studies) and the ability to articulate methodology choices and limitations.

• Quantitative Research Acumen: Experience with quantitative methods (e.g., surveys, A/B testing analysis, statistical analysis of user data) and understanding how to integrate quantitative findings with qualitative insights.

• Product Strategy Influence: Proven ability to connect customer needs and behaviors to product strategy, business objectives, and go-to-market plans.

• AI Fluency & Application: Demonstrated experience and clear examples of applying AI tools and techniques within research processes to drive impact and efficiency.

• Cross-functional Collaboration: Strong track record of building trust and working effectively with product managers, designers, engineers, and marketing teams.

• Business Judgment & Decision Making: Ability to understand business goals, make sound judgments on research rigor versus speed, and drive consensus on difficult tradeoffs.

• Data Synthesis & Insight Generation: Skill in combining qualitative research, product usage data, and other relevant information to form comprehensive problem understanding and identify actionable opportunities.

Preferred Skills:

• Experience with product analytics tools and platforms for analyzing user behavior data.

• Familiarity with cloud data platforms or enterprise software markets.

• Experience in fast-paced, high-growth technology environments.

• Ability to mentor junior researchers and contribute to the growth of the research practice.

📝 Enhancement Note: The requirements strongly emphasize practical experience and impact. The "AI Fluency & Application" is a critical differentiator, as is the ability to integrate diverse data sources (qualitative, quantitative, product usage, AI-generated insights).

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Impactful Case Studies: Present 2-3 detailed case studies showcasing your research process from problem definition to outcome. Each case study should clearly articulate the research question, methodology, your specific role, key insights, and the resulting product or business impact.

• Methodological Diversity: Demonstrate expertise across a range of qualitative and quantitative methods, explaining why specific approaches were chosen for different project needs.

• Data Integration Examples: Include examples of how you've synthesized multiple data sources (e.g., user interviews, survey data, product analytics, AI-driven insights) to build a holistic understanding of a problem.

• AI Integration Showcase: Specifically highlight instances where you've intentionally leveraged AI tools or methodologies in your research process and the tangible benefits or outcomes achieved.

Process Documentation:

• Research Planning & Scoping: Showcase your ability to define research objectives that align with business goals and product strategy, and to scope projects effectively within timelines.

• Methodology Design: Provide examples of how you design research plans, select appropriate methods, and develop research instruments (e.g., interview guides, survey questionnaires).

• Insight Synthesis & Communication: Demonstrate your process for analyzing raw data, synthesizing findings into clear, compelling insights, and communicating these effectively to diverse stakeholders.

• Impact Measurement: Show how you track and communicate the impact of your research on product decisions, user experience improvements, and business outcomes.

📝 Enhancement Note: The portfolio is critical for this role, serving as the primary evidence of the candidate's ability to deliver impact. Emphasis on AI integration within case studies is a key requirement.

💵 Compensation & Benefits

Salary Range: Based on the provided range of $173,000 to $248,400 USD annually, this compensation is competitive for a Senior User Researcher in the Bellevue, Washington area, reflecting the role's seniority, strategic impact, and the high cost of living in the region.

Benefits:

• Comprehensive health, dental, and vision insurance plans.

• Generous paid time off (PTO) and company holidays.

• 401(k) retirement savings plan with company match.

• Stock options or equity grants.

• Professional development and learning opportunities, including conference attendance and training.

• Wellness programs and resources.

• Parental leave policies.

• Potential for performance-based bonuses.

Working Hours: Standard full-time working hours (approximately 40 hours per week), with flexibility for remote work within the United States. Occasional adjustments may be necessary to accommodate cross-functional team needs or urgent research requirements, particularly when working with global teams.

📝 Enhancement Note: The salary range is explicitly provided and is typical for senior-level tech roles in major tech hubs like the Seattle metropolitan area. The benefits package is assumed to be comprehensive, aligning with industry standards for a company of Snowflake's caliber.

🎯 Team & Company Context

🏢 Company Culture

Industry: Cloud Computing / Data Warehousing / Data Cloud. Snowflake operates at the forefront of the data cloud revolution, providing a leading platform for data storage, processing, and analytics. This context means the company values innovation, data-driven decision-making, and a deep understanding of complex technical products and their users.

Company Size: Snowflake is a large, publicly traded technology company with thousands of employees globally. This size offers opportunities for impact within a significant organization, access to extensive resources, and exposure to a wide range of professional development avenues.

Founded: Snowflake was founded in 2012. Its relatively recent founding, coupled with rapid growth, suggests a dynamic, fast-paced culture that embraces change and encourages experimentation.

Team Structure:

• The User Research team likely operates within the Product or Design organization, with researchers embedded in specific product areas or working on cross-functional initiatives.

• Researchers partner closely with Product Managers, Designers, Engineers, and Marketing Leads, forming cross-functional "squads" or "pods" focused on specific product domains or strategic objectives.

• This role reports into a research lead or director, with opportunities for mentorship and collaboration with peers across the organization. Methodology:

• Data-Driven Decision Making: Snowflake emphasizes using data to inform all aspects of the business, including product development and strategy. User research is a critical component of this, providing the qualitative and quantitative understanding of user needs.

• Agile & Iterative Development: The company likely employs agile methodologies, requiring researchers to be adaptable, deliver insights iteratively, and work closely with development cycles.

• AI-First Mindset: The company is actively promoting an "AI-native" culture, encouraging employees to treat AI as a collaborator and to find innovative ways to leverage it across functions. This will be a key aspect of how research is conducted and its impact is measured.

Company Website: https://www.snowflake.com/

📝 Enhancement Note: The company's focus on the "agentic enterprise" and AI integration is a significant cultural indicator. This role requires a candidate who is not only a skilled researcher but also an early adopter and thoughtful practitioner of AI in their work.

📈 Career & Growth Analysis

Operations Career Level: This Senior User Researcher role is positioned as an experienced individual contributor with significant autonomy and influence. It requires the ability to lead complex research initiatives, mentor others, and directly impact product and business strategy. It's a critical role for shaping user experience and informing high-stakes decisions.

Reporting Structure: The role will likely report to a User Research Lead or Director within the Product organization. Collaboration will be extensive with Product Management, UX Design, Engineering, and Marketing teams, requiring strong stakeholder management skills.

Operations Impact: The impact of this role is substantial, directly influencing the direction of Snowflake's products and go-to-market strategies. By deeply understanding customer needs and leveraging AI for enhanced insights, the Senior User Researcher will drive product-market fit, improve user adoption, and contribute to revenue growth and customer satisfaction.

Growth Opportunities:

• Leadership in Research Craft: Opportunity to lead larger, more complex research programs, mentor junior researchers, and contribute to the advancement of research methodologies within Snowflake.

• Strategic Product Influence: Deepen expertise in specific product areas and gain greater influence over product roadmaps and strategic decision-making.

• AI Specialization: Develop advanced skills in applying AI to user research, potentially becoming a go-to expert in this emerging area within the company.

• Cross-functional Leadership: Potentially transition into product management or design leadership roles by leveraging deep user understanding and strategic insight.

📝 Enhancement Note: The growth path emphasizes both deepening research expertise and expanding strategic influence, with a clear opportunity to become a leader in AI-driven research.

🌐 Work Environment

Office Type: This role is designated as hybrid, with the option for remote work within the United States. This suggests a flexible work environment that balances in-person collaboration with the benefits of remote productivity.

Office Location(s): The primary location is Bellevue, Washington. However, the "TELECOMMUTE" and "United States" location requirements indicate that remote employees within the US are a strong possibility for this role.

Workspace Context:

• Collaborative Spaces: The hybrid model implies access to office spaces designed for collaboration, team meetings, and focused work, fostering interaction with colleagues.

• Technology-Enabled: As a leading tech company, expect access to modern collaboration tools, high-performance computing resources, and the latest software for research and analysis.

• Data-Centric Environment: Working at Snowflake means being immersed in a data-rich environment where insights are highly valued and actively sought.

Work Schedule: A standard 40-hour work week is expected, with a degree of flexibility to accommodate project needs and team collaboration. This flexibility is crucial for user researchers who often need to schedule interviews and studies around participant availability.

📝 Enhancement Note: The hybrid nature and US-wide remote consideration offer significant flexibility, appealing to candidates who value work-life balance while remaining part of a dynamic team.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will review your application and resume, focusing on experience, AI fluency, and research impact.

• Hiring Manager Interview: A discussion focused on your background, research philosophy, approach to AI in research, and experience with cross-functional collaboration.

• Portfolio Presentation: A dedicated session where you will present 1-2 key case studies from your portfolio, detailing your process, insights, and impact. Be prepared to discuss your methodology choices, challenges, and how AI was integrated.

• Cross-functional Interviews: Interviews with Product Managers, Designers, and potentially Engineers to assess your collaboration skills, ability to influence, and understanding of product development cycles.

• Research Team Interview: A discussion with other researchers to evaluate your research craft, problem-solving skills, and cultural fit within the user research team.

Portfolio Review Tips:

• Focus on Impact: Clearly articulate the business or product outcomes that resulted from your research. Quantify impact whenever possible (e.g., increased conversion rates, reduced support tickets, improved user satisfaction scores).

• Showcase AI Integration: Dedicate specific sections or examples within your case studies to demonstrate how you've thoughtfully applied AI in your research workflow and the benefits derived.

• Methodological Justification: Be prepared to explain why you chose certain research methods over others, detailing the tradeoffs and why your approach was sufficient for the decision at hand.

• Storytelling: Structure your case studies as compelling narratives that highlight your problem-solving process, your strategic thinking, and your ability to drive change.

• Conciseness and Clarity: Ensure your portfolio is well-organized, easy to navigate, and presents information clearly and concisely.

Challenge Preparation:

• Hypothetical Research Scenario: You might be asked to outline a research plan for a new product feature or to address a specific business problem, demonstrating your strategic thinking and methodological approach, including AI integration.

• Behavioral Questions: Prepare for questions about how you handle conflict, manage stakeholders, deal with ambiguity, and integrate feedback.

• AI Application Discussion: Be ready to discuss your perspective on the future of AI in user research and specific examples of how you envision or have implemented its use.

📝 Enhancement Note: The interview process is designed to rigorously assess research craft, strategic thinking, collaboration abilities, and practical application of AI. A well-prepared portfolio is paramount.

🛠 Tools & Technology Stack

Primary Tools:

• Research Platforms: Tools for conducting and analyzing qualitative and quantitative research (e.g., UserTesting.com, Lookback, Maze, Qualtrics, SurveyMonkey).

• Collaboration Suites: Integrated platforms for communication and project management (e.g., Slack, Microsoft Teams, Jira, Confluence).

• Design & Prototyping Tools: Familiarity with tools used by design partners (e.g., Figma, Sketch, Adobe XD) for context and collaboration.

Analytics & Reporting:

• Product Analytics: Tools for analyzing user behavior data (e.g., Amplitude, Mixpanel, Pendo).

• Data Visualization: Tools to create dashboards and reports (e.g., Tableau, Power BI, Looker).

• Statistical Software: For deeper quantitative analysis (e.g., R, Python libraries, SPSS).

CRM & Automation:

• AI-Powered Research Assistants: Tools that leverage AI for tasks like interview transcription, sentiment analysis, summarization, and identifying themes.

• Data Warehousing/Analysis Tools: Given Snowflake's product, familiarity with how data is stored and accessed will be beneficial, though direct use of Snowflake's platform may not be required for this role.

📝 Enhancement Note: Proficiency with a range of research and analytics tools is expected. A key differentiator will be experience with AI-powered tools that augment the research process, reflecting the company's AI-first mandate.

👥 Team Culture & Values

Operations Values:

• Customer Obsession: A deep commitment to understanding and advocating for the customer's needs, ensuring their voice guides product development and strategy.

• Innovation & Experimentation: A culture that encourages trying new approaches, embracing new technologies (especially AI), and learning from both successes and failures.

• Collaboration & Transparency: Working effectively across teams, sharing insights openly, and building consensus through open communication and shared understanding.

• Data-Driven Impact: Valuing data in all its forms – qualitative, quantitative, and usage metrics – to drive informed decisions and measure the impact of work.

• Agility & Speed: The ability to move quickly, adapt to changing priorities, and deliver valuable insights in a fast-paced environment.

Collaboration Style:

• Embedded Research: Researchers are integrated into product teams, working day-to-day with PMs, Designers, and Engineers.

• Partnership Approach: Building strong, trusted relationships with cross-functional partners is key, acting as a strategic advisor rather than just a service provider.

• Insight Sharing: Proactive sharing of findings through presentations, documentation, and informal discussions to ensure insights are widely understood and acted upon.

• Feedback Culture: An environment where constructive feedback is welcomed and exchanged to continuously improve research processes and outcomes.

📝 Enhancement Note: The emphasis on AI as a collaborator and the "agentic enterprise" concept will likely permeate the team's values, promoting a forward-thinking and experimental approach to research.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapidly Evolving AI Landscape: Staying current with the fast-paced advancements in AI tools and techniques applicable to user research, and discerning which are genuinely valuable.

• Balancing Rigor and Speed: Delivering high-quality research insights within tight product development timelines, especially in a fast-moving tech company.

• Influencing Complex Stakeholders: Earning trust and driving consensus among senior leaders with diverse priorities and perspectives.

• Integrating Diverse Data Sources: Effectively combining qualitative insights, quantitative data, product usage metrics, and AI-generated findings into a coherent narrative.

Learning & Development Opportunities:

• AI in Research Specialization: Opportunities to become a leader in applying AI to user research, potentially leading workshops or developing best practices for the company.

• Advanced Methodologies: Deepen expertise in specialized research methods or quantitative analysis techniques.

• Product Strategy Acumen: Gain deeper understanding of Snowflake's business, market, and product strategy, enhancing your ability to contribute at a strategic level.

• Mentorship & Leadership: Develop leadership skills through mentoring junior researchers and potentially leading research initiatives or programs.

📝 Enhancement Note: The challenges are directly tied to the innovative and fast-paced nature of Snowflake and the broader tech industry, particularly around AI adoption. Growth opportunities focus on specialization and strategic impact.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you used AI to significantly improve your user research process or uncover novel insights. What was your approach, and what were the results?" (Focus on deliberate application, methodology, and measurable impact.)

• "How would you approach setting research priorities for a new product initiative at Snowflake, given limited resources and competing demands from product, design, and engineering?" (Highlight your process for alignment, trade-offs, and linking research to business goals.)

• "Walk us through a complex product or go-to-market decision that was significantly influenced by your research. What were the key insights, and how did you build consensus among stakeholders?" (Emphasize your ability to translate research into actionable strategy and drive change.) Company & Culture Questions:

• "What excites you about Snowflake's mission to power the 'agentic enterprise,' and how do you see user research contributing to this vision?" (Show your understanding of the company's direction and your role within it.)

• "How do you ensure customer needs are prioritized in a fast-paced, data-driven environment like Snowflake?" (Demonstrate your advocacy for the user and your methods for integrating user insights into decision-making.)

• "Describe your experience working with AI as a collaborator. What are the ethical considerations and best practices you follow?" (Assess your maturity and thoughtfulness in using AI.) Portfolio Presentation Strategy:

• Structure for Impact: For each case study, clearly define the problem, your role, your research methodology (including AI integration), key insights, and the tangible outcomes. Use visuals where appropriate.

• Quantify Whenever Possible: Present metrics and data that demonstrate the impact of your work on product decisions, user experience, or business results.

• Articulate AI Value: Be explicit about how AI enhanced your research – was it for efficiency, deeper analysis, new types of insights, or something else?

• Showcase Collaboration: Highlight how you partnered with cross-functional teams throughout the research process.

• Be Ready for Deep Dives: Anticipate questions about your methodology choices, limitations, and alternative approaches.

📝 Enhancement Note: Preparation should focus on demonstrating a blend of deep research craft, strategic thinking, practical AI application, and strong collaboration skills, all backed by concrete examples from your portfolio.

📌 Application Steps

To apply for this Senior User Researcher position:

• Submit your application through the provided link on Ashby.

• Portfolio Customization: Tailor your resume and portfolio to specifically highlight your experience with qualitative and quantitative research, your successful application of AI in research processes, and examples of how your work has driven product and business outcomes.

• Resume Optimization: Ensure your resume clearly states your years of industry experience, lists key research methodologies and tools, and uses action verbs to describe your responsibilities and achievements, with a specific emphasis on influencing decisions and collaborating cross-functionally.

• Interview Preparation: Practice articulating your case studies, focusing on the "why" behind your methodological choices, the impact of your findings, and your specific contributions, especially regarding AI integration. Prepare thoughtful questions about Snowflake's research practice and AI strategy.

• Company Research: Thoroughly research Snowflake's products, recent news, and their stated vision for the "agentic enterprise." Understand their competitive landscape and how user research contributes to their success.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

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