Financial Analyst, Marketing

Strategic Finance - Product, AI/ML and Analytics

Snowflake

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 SNOWFLAKE 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 Strategic Finance is the commercial and analytical engine behind Snowflake's product and revenue decisions. The team operates at the intersection of product strategy, pricing, and investment prioritization. Product Finance, the function this role sits within, partners with each product organization on planning, performance, and pricing. We work closely with Product and Engineering leadership, and we partner across Sales, Business Development, and the Executive Leadership Team. Every consequential AI and Analytics investment, monetization, and pricing decision at Snowflake runs through analysis this team produces. ABOUT THE ROLE We are hiring a senior strategic finance thought partner to help shape Snowflake's AI and Analytics workloads, the company's fastest-growing and most strategically complex product surface. You will partner closely with Product, Engineering, Marketing, and Sales leadership to set strategy, evaluate growth bets, lead pricing and packaging decisions, and build the financial rigor that lets these workloads scale. You will translate product usage, customer behavior, unit economics, and market signals into decisions on what we build, how we launch, how we monetize, and where we invest. You will help define the growth model for a frontier AI product portfolio while working at the intersection of strategy, finance, and technology. This is a people manager role. IN THIS ROLE YOU WILL * Strategic Finance Thought Partnership. Serve as the strategic finance partner to Cortex, Notebooks, Machine Learning, and Analytics product and engineering leaders. Help shape product strategy, growth priorities, pricing decisions, and investment tradeoffs. * Forecast and Performance Ownership. Own the forecast for AI and Analytics workloads, including revenue, usage, margin, unit economics, leading indicators, and the operating metrics that show where each workload is gaining or losing traction. * Pricing and Monetization Leadership. Lead pricing and monetization strategy for AI workloads. Set pricing principles, packaging, metering, and commercial terms across inference, training, embedded models, and AI-native applications. Bring willingness-to-pay research, competitive benchmarks, and unit economics into pricing decisions. Land emerging AI commercial structures as they graduate from incubation to scaled go-to-market. * Translate Data Into Decisions. Translate product usage, customer behavior, cohort and funnel dynamics, and financial data into clear recommendations that influence long-term strategy and day-to-day product calls. * Investment Business Cases. Build decision-ready business cases for major AI and Analytics product and go-to-market investments. Return on investment, investment sizing, risk framing, comparative tradeoffs. * Build Planning and Performance Systems. Build the forecast methodology, key performance indicator architecture, decision frameworks, executive narratives, and repeatable reporting that help the team move faster as the workloads scale. * People Leadership. Manage and develop a small team of analysts. Set the bar for analytical rigor, executive communication, and product judgment. Cultivate a team that operates as a credible thought partner to Product and Engineering. * Market Intelligence. Stay current on AI, software-as-a-service, product-led growth, consumption-based pricing, and competitive dynamics. Inform where Snowflake should invest in AI workloads and how the business model should evolve as AI changes the playbooks. * Executive Narratives. Prepare and deliver high-quality executive and Board materials that connect business performance, product strategy, key risks, and strategic recommendations. WHAT YOU WILL NEED REQUIRED * 8+ years of experience in investment banking, management consulting, strategic finance, product finance, growth finance, or buy-side investing, coupled with operating experience at a fast-paced, scaling technology company. * Experience supporting product teams on growth, pricing, packaging, monetization, or product strategy decisions, ideally in product-led growth, growth-stage software-as-a-service, consumption-based, or usage-based business models. * Exceptional analytical and financial modeling skills, including building product profit and loss views, operating models, cohort and funnel analyses, pricing models, and unit economics that connect strategy to growth decisions. * Strong business judgment and product instincts. Ability to evaluate opportunities, tradeoffs, and risks in a fast-moving product environment. * Working understanding of AI and machine learning infrastructure and economics: model lifecycle, inference vs. training cost structures, AI commercial models. Curiosity about how AI products change the pricing and packaging playbooks. * The ability to translate complex product, usage, customer, and financial data into clear recommendations for Product teams and senior leadership. * High attention to detail and a commitment to accuracy, paired with comfort making decisions when data is imperfect and the business is evolving. * People management experience. Demonstrated track record of hiring, developing, and retaining strong analytical talent. * SQL fluency. Comfort working directly with product analytics datasets in a cloud data platform. * Effective communication. Capable of producing executive-quality narratives that survive Executive Leadership Team and Board review on first submission. * Bachelor's degree in Finance, Economics, Computer Science, Engineering, or related discipline. MBA preferred. PREFERRED * Hands-on experience with AI and machine learning product economics at a high-growth company (foundation model provider, AI infrastructure, AI applications, or a major cloud's AI portfolio). * Familiarity with consumption-based and usage-based pricing in cloud, data, or AI platforms. * Experience building business cases and growth models for new product categories where commercial mechanics are not yet standardized. * Experience with competitive AI pricing analysis and willingness-to-pay research. * Python proficiency for data analysis. LOCATION Menlo Park, CA. Snowflake HQ office. This role requires in-person attendance at least 3 days per week. Location is strict. COMPENSATION The estimated base salary range for this role is $250,000 to $320,000, this role is eligible to participate in Snowflake’s bonus and equity plan. The successful candidate's starting compensation will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. EQUAL OPPORTUNITY STATEMENT Snowflake is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to age, color, gender identity or expression, marital status, national origin, disability, protected veteran status, race, religion, pregnancy, sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. 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

Strategic Finance Analyst

Snowflake

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: We exist to improve Product leaders' understanding and decision-making on how to profitably grow the business. Our North Star is to increase workload contribution margin dollars above the current forecast by serving as an objective, full-stack business partner. We do this by measuring key metrics, inferring actionable insights, catalyzing strategic decisions, and accelerating operational efficiency across Product, Engineering, and Sales. ABOUT THE ROLE: This is a high-visibility role that sits at the intersection of product strategy and financial analysis, giving you a unique vantage point to influence how we scale our business. We aren't looking for someone to just execute tasks and pull data; we need someone eager to learn, grow, and contribute as a business partner who can navigate ambiguity and anticipate next steps. This role is ideal for recent graduates or early-career professionals with strong analytical instincts, business curiosity, and a desire to make an impact. You will work on critical projects and collaborate with senior leaders to turn complex data into decisive action. WHAT YOU WILL DO: * Support Financial Model Development Contribute to the building and maintenance of financial models that track both revenue and cost drivers, enabling accurate forecasting and real-time visibility into workload contribution margins. * Contribute to Revenue & Margin Insights Assist in analyzing historical and forward-looking trends for revenue, COGS, and margin to support actionable recommendations that influence pricing, packaging, and go-to-market strategies. * Support Pricing Strategy Analysis Help analyze usage patterns, customer segments, and willingness to pay to support pricing and packaging decisions. Contribute data-driven analysis that balances growth and margin, and assist in measuring the impact of pricing changes. Partner with Product, Finance, and Sales to understand and operationalize pricing strategies. * Collaborate with PMs and Sales Work alongside Engineering, Product Managers, and Sales to evaluate new product features or market opportunities. Support business case development by providing data-driven insights into revenue potential and profitability. Communicate complex technical or financial concepts in a succinct, easy-to-understand manner to stakeholders at all levels. * Data-Driven Insights (SQL) Find the "why" behind the numbers. You will go beyond the surface by learning our complex data structures and business drivers. By developing proficiency in navigating our schemas and tables, you'll ensure that you deliver timely and accurate insights. * Accelerate Insights with AI Leverage Snowflake Intelligence and AI-assisted SQL daily to automate manual reporting and speed up your insight discovery process. You will use our native AI features to streamline complex workflows, allowing you to focus less on manual data prep and more on contributing strategic insights. * Help Build Scalable Reporting & Tooling Translate your data findings into automated, high-visibility dashboards that Product and Finance leaders rely on for decision making. The dashboards you build will be maintained by Snowflake's business intelligence team. * Assist in Cloud Spend & Infrastructure Optimization While revenue is your focus, you'll also help identify and flag abnormalities in infrastructure spend to maintain healthy margins. Support recommendations to reduce COGS/OpEx and improve cost efficiency. WHAT YOU WILL NEED: * Bachelor's Degree: In Finance, Data Science, Computer Science, Economics, or a related field. Strong academic foundation in quantitative analysis is valued. * 1–2 Years of Experience: Recent graduates or candidates with up to 1 year of professional experience. Relevant internships, capstone projects, or academic research in Finance, Consulting, Data Analytics, or related fields count. Exposure to SaaS, Cloud, Data, or Fintech environments is a plus. * Analytical Aptitude & Learning Mindset: Demonstrated ability to work with quantitative and qualitative data through coursework, projects, or internships. You may not have built production financial models yet, but you've shown the aptitude and eagerness to learn quickly. * Technical Agility (SQL preferred, but not required): You have a high aptitude for navigating technical systems and data structures. While you don’t need to be a SQL expert on day one, you possess the ability to quickly become proficient in understanding complex schemas and data logic. Any prior experience with coding languages is a significant plus. * Exposure to Revenue & Business Analysis: Familiarity with concepts like revenue, COGS, and margin analysis from work experience, coursework, case competitions, or internships. Experience with Salesforce or other business systems is a bonus, not a requirement. * Ownership & Problem-Solving Mindset: Adept at working through ambiguity and taking initiative—whether in a team project, internship, or academic setting. You anticipate next steps, coordinate with others, and push projects forward. * Exceptional Communication: Able to translate complex data into clear takeaways. Comfortable presenting findings to peers and senior stakeholders. * Continuous Improvement Mentality: You're always looking for ways to optimize. The first version of your work is never your last—you believe there's always a better way. 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

Senior/ Staff Analyst, Finance Analytics & AI

Snowflake

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 ROLE We are an AI-first analytics team. We don't use AI to augment traditional BI workflows — we've replaced them. The Finance Analytics team builds the intelligence layer that Strategic Finance runs on: AI agents that encode repeatable finance processes, Streamlit apps that surface real-time insight, semantic models that let any analyst query complex data in plain English, and workflow automations that collapse hours of manual work into a single prompt. Our primary development environment is CoCo (Cortex Code), Snowflake's AI coding assistant, and SnowWork, the AI IDE we ship work in. Every deliverable on this team is built AI-first: you design the workflow, you write the prompt, you validate the output. If you are still building dashboards by hand, refreshing Excel files manually, or treating AI as a spell-checker for your code — this role will ask you to operate differently. This is a high-breadth seat. One week you're building a new AI agent for quarterly revenue analysis; the next you're designing a sensitivity analysis tool for an earnings war room. You are equally comfortable in an AI-IDE, a Python file, and a stakeholder summary for a senior finance leader. WHAT YOU'LL WORK ON AI AGENT AND WORKFLOW DEVELOPMENT (PRIMARY FOCUS) * Design and build skills and agentic experiences that encode repeatable finance workflows — revenue analysis, cost monitoring, earnings prep, headcount tracking — into reusable, invokable tools using CoCo and CoWork * Write and iterate on prompt & skill structures (YAML + Markdown skill files) based on output quality and stakeholder feedback * Build skills that allows non-technical finance analysts to produce analyst-quality output in a single prompt * Evaluate model outputs rigorously — you are the quality gate before anything reaches a finance stakeholder FINANCE ANALYTICS * Build and maintain quarterly and weekly revenue summary pipelines * Support sensitivity analysis models for quarterly business reviews & revenue forecast scenarios * Produce ad-hoc analysis for Strategic Finance SEMANTIC LAYER & APPLICATION DEVELOPMENT * Own semantic layers end-to-end — model design, versioning strategy, verified query coverage, and accuracy iteration based on eval metrics; not just build models, but maintain the contract between the model and its consumers across each quarterly iteration * Develop and deploy production finance dashboards as Streamlit apps (locally and deployed to Snowflake) * Build customer-facing demo applications for Sales and Field teams * Apply reusable component patterns and shared utility libraries for consistent, polished UI EARNINGS AND REPORTING AUTOMATION * Participate in quarterly earnings cycle prep — scenario tooling, export automation, IR data requests * Build and maintain source-of-truth reporting exports (multi-tab Excel, formatted to spec) * Support ad-hoc disclosure and investor relations data needs during quarter-end HARD SKILLS REQUIRED MUST-HAVE AI-assisted development — You have used an LLM coding assistant (CoCo, Cursor, GitHub Copilot, Claude, or equivalent) as your primary development tool. You know how to write a prompt that produces production-ready output, how to steer a model that's heading in the wrong direction, and how to encode domain logic into a reusable, parameterized skill. You have a measurable, trackable record of daily AI usage. Prompt engineering and skill authoring — You can write a structured prompt (YAML + Markdown or equivalent) that routes correctly 95% of the time, handles edge cases gracefully, and encodes enough domain knowledge that the model behaves like a subject matter expert. You think in terms of context, instructions, examples, and output format — not just "the thing I typed before the code came out." Python — Modern, type-hinted, readable. You write Python-based applications, data pipelines, and reporting automation. You understand caching, session state, and how to structure a multi-page app cleanly. At the senior level: you've contributed to a shared library or package that others depend on, and you've designed agent orchestration systems — including parallel agent patterns with synthesis layers. SQL — CTEs, window functions, incremental pipeline patterns. You don't look up the syntax for a row-numbered deduplication. Data modeling fundamentals — You understand bronze, silver, and gold data models conceptually and contribute to the gold layers and how they translate to semantic layer. You know not just how to build a model, but how to version it, evaluate SQL generation accuracy, maintain a verified query library, and iterate based on real analyst feedback. A non-technical user should be able to query your model in plain English and get a correct answer. STRONG PLUS * Snowflake Cortex — Cortex Analyst, Cortex Agents, AI_SUMMARIZE, AI_EXTRACT, Dynamic Tables, semantic views * SnowWork / CoCo — Prior experience deploying agents, authoring skill files, or working within the Snowflake Intelligence ecosystem * Finance literacy — You can read a revenue waterfall, distinguish ARR from NRR, and explain what drives a QoQ change in product revenue * Reporting automation — openpyxl, multi-tab Excel exports formatted to spec, named ranges * dbt — Model authoring, ref() patterns, YAML tests in a cloud warehouse context * Semantic search / embeddings — Vector similarity, embedding-based retrieval, and how they power natural language analytics SOFT SKILLS REQUIRED TRANSLATES BETWEEN AI, DATA, AND FINANCE Your stakeholders are financial analysts and senior directors who think in Excel models and board decks. You write prompts and code, but your output needs to make sense to someone who has never opened a terminal. You are the translation layer between what the model can do and what finance actually needs. You communicate complex ideas simply, ensuring stakeholders understand, trust, and can act on what you build. You are the translation layer between what the model can do and what finance actually needs. You set the standard for how agents are built on this team. Junior analysts look to your skills and code as the reference implementation. You push back on shortcuts that create maintenance debt. You don't wait to be asked to improve shared infrastructure. THINKS IN WORKFLOWS, NOT TASKS You don't just answer a question — you build a tool that answers it forever. When asked to do something twice, you automate it. Your instinct is to encode work into a reusable agent, not to redo it manually each week. At the senior level, this extends to the team: when the team does something repeatedly, you build the shared infrastructure that makes everyone faster. WORKS FAST WITH HIGH ACCURACY The role runs on a weekly cadence tied to finance deliverables. You scope, build, and ship a working artifact in 1–2 days. Accuracy matters more than speed — but accuracy is not a reason to be perpetually slow. COMFORTABLE WITH AMBIGUITY The brief is often: "Can you build something like the earnings tool, but for sensitivity analysis?" You scope it, build a working prototype, and come back for feedback — not a list of clarifying questions. MINIMUM REQUIREMENTS * 3-5+ years of experience in analytics, data engineering, or a technical finance adjacent role * Has used an AI coding assistant as a primary development tool — daily usage, not occasional * Proficient in SQL — you can write a window function without looking it up * Has shipped multiple Python applications that end-users actually interacted with; at least one is actively maintained in production * Comfortable working in Git (PRs, branches, code review) * Familiar with fiscal year concepts and core revenue metrics (ARR, bookings, NRR) WHAT SUCCESS LOOKS LIKE AT 90 DAYS * You've taken ownership of the quarterly and weekly revenue analysis workflows — they run correctly on schedule without hand-holding * You've shipped at least one Streamlit app to production or a demo application to the Finance Workloads team * You've participated in at least one quarterly earnings cycle * You've contributed a module, skill, or shared component to the team's shared infrastructure — something other analysts use without you having to explain it WHY THIS ROLE IS UNUSUAL AT THIS LEVEL This seat asks you to do all of that and build the AI infrastructure that makes the entire Finance Analytics team faster. You are simultaneously a practitioner and a workflow engineer. If you are fluent with AI development tools, you can punch significantly above your level. At the senior level, you are not just building the infrastructure — you are deciding what it should be. That means making architectural calls that hold across quarters, not just shipping the next feature. 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