分析工程师，增长团队
Analytics Engineer, GTM
职位描述
作为市场拓展（Go-to-Market）组织数据团队的一员，你将帮助建立以数据驱动的文化，提升决策能力，并通过分析推动战略计划的实施。
这是一个涵盖数据建模、指标定义、可视化、分析和自助工具的全栈数据岗位。你将构建可信赖、可扩展的数据源和产品，为业务提供可靠、可操作的洞察。这项工作需要判断力：你将根据每个问题的情况，选择最适合的工具、方法和投入程度，从聚焦的分析到持久的生产级数据产品。
作为市场拓展组织的核心合作伙伴，你将解决基础性和临时性的分析需求。你将把复杂的数据转化为清晰的叙述，帮助技术人员和非技术人员理解发生了什么、为什么重要以及他们接下来应该做什么。
在该职位中，你将：
- 与市场拓展团队紧密合作，主动识别高影响力的问题，并将业务需求转化为数据模型、指标、分析和可扩展的技术解决方案。
- 定义、获取、验证并实现指导业务的指标，帮助团队将其纳入规划和日常决策中。
- 领导跨职能的数据项目，覆盖已有的和新兴的业务领域，包括为新领域制定数据策略。
- 构建可扩展的数据模型和流程，将来自多个来源的数据整合并转换为可信、易访问的数据集。
- 创建仪表盘、报告、分析工具和其他数据产品，使利益相关者能够独立回答问题。
- 负责指标、分析模型和数据产品的生命周期，从最初的探索和原型设计到生产环境和持续维护。
- 根据受众、紧迫性、复杂性和预期价值，为每个问题选择最有效的方法——无论是分析、指标、数据模型、可视化还是自助产品。
- 在优先处理竞争性请求时展现出强大的判断力，平衡即时的业务需求与提升数据生态系统长期质量和可扩展性的投资。
- 使用AI辅助开发工具提高生产力，同时保持代码、数据模型和文档的清晰、测试和可维护性。
- 通过演示、书面备忘录、仪表盘和其他方式，将复杂的发现转化为清晰且有说服力的叙述。
查看英文原文
ABOUT THE ROLE
As a member of the Data team within the Go-to-Market organization, you will help build a data-driven culture, improve decision-making, and advance strategic initiatives through analytics.
This is a full-stack data role spanning data modeling, metric definition, visualization, analysis, and self-service tooling. You will build trusted, scalable data sources and products that give the business reliable, actionable insights. The work calls for judgment: you will choose the tool, approach, and level of investment that best fit each problem, from a focused analysis to a durable production data product.
As a core partner to the GTM organization, you will address both foundational and ad hoc analytics needs. You will turn complex data into clear narratives that help technical and non-technical audiences understand what is happening, why it matters, and what they should do next.
IN THIS ROLE, YOU WILL
- Partner closely with GTM teams to proactively identify high-impact questions and translate business needs into data models, metrics, analyses, and scalable technical solutions.
- Define, source, validate, and operationalize the metrics that guide the business, helping teams incorporate them into planning and day-to-day decisions.
- Lead cross-functional data projects across established and emerging business areas, including setting the data strategy for greenfield domains.
- Build scalable data models and pipelines that integrate and transform data from multiple sources into trusted, accessible datasets.
- Create dashboards, reports, analytical tools, and other data products that enable stakeholders to answer questions independently.
- Own the lifecycle of metrics, analytical models, and data products from initial exploration and prototyping through production and ongoing maintenance.
- Choose the most effective approach for each problem—whether an analysis, metric, data model, visualization, or self-service product—based on the audience, urgency, complexity, and expected value.
- Exercise strong judgment when prioritizing competing requests, balancing immediate business needs with investments that improve the long-term quality and scalability of the data ecosystem.
- Use AI-assisted development tools to increase productivity while maintaining clear, tested, and maintainable code, data models, and documentation.
- Turn complex findings into clear, persuasive narratives through presentations, written memos, dashboards, and other formats suited to the audience.
YOU MIGHT THRIVE IN THIS ROLE IF YOU
- Have 10+ years of experience in a relevant data role within fast-moving, results-oriented organizations.
- Can independently structure and own ambiguous, high-impact business problems from initial framing through recommendation and execution.
- Are highly autonomous, resourceful, and creative when navigating technical, operational, and stakeholder constraints.
- Exercise strong judgment when deciding what to prioritize, how deeply to invest, and when a quick answer should become a durable data product.
- Have deep SQL expertise and extensive experience working with large datasets and designing ETL workflows.
- Understand effective software and analytics engineering practices and can use AI tools to move faster without creating brittle systems, unclear code, or unnecessary complexity.
- Are proficient in a quantitative programming language, preferably Python.
- Have experience with BI tools such as Tableau or Looker and know how to enable effective self-service analytics.
- Have worked with custom visualization frameworks such as React, Streamlit, or Plotly Dash.
- Can turn complex analysis into persuasive stories using memos, presentations, dashboards, and other formats.
- Bring exceptional attention to detail and a strong commitment to accuracy.
- Have delivered significant business impact, ideally within Sales, Finance, Support, or another GTM function.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
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