岗位能力对标
OpenAI

IT Controls Data Engineer

San Francisco · 全职 · 数据与分析

岗位更新:2026-05-29资料抓取:2026-08-04查看原始招聘来源

需要对标的能力

Agent 工程 · Harness / 脚手架

岗位职责与要求

About the Team The IT and Security organization builds the systems, data foundations, and automation that help OpenAI operate securely and reliably at scale. We support critical domains across identity, access, infrastructure security, enterprise systems, and internal productivity. As OpenAI grows, audit readiness and control assurance increasingly depend on reliable data: accurate system inventories, access populations, change records, configuration state, exception signals, and evidence generated directly from source systems. Our goal is to move beyond manual evidence collection and build scalable data products, automated validation, and continuous control monitoring that make security and IT controls measurable, repeatable, and defensible. About the Role We are looking for an IT Controls Data Engineer to build the data infrastructure that powers audit readiness, IT controls, evidence automation, and continuous control monitoring. In this role, you will design and maintain the pipelines, datasets, models, validation logic, dashboards, and evidence exports that make IT controls measurable, repeatable, and defensible. You will work across Security, IT, Infrastructure, Engineering, Finance Risk Management, and auditors to turn complex system behavior into reliable control data products. This is a technical builder role. The ideal candidate is strong in data engineering and analytics engineering, comfortable working with enterprise and security system data, and able to explain data lineage, source-system behavior, and control logic clearly to technical and audit stakeholders. You’ll be responsible for - Building reliable data pipelines, models, and datasets for IT controls, including access, identity, configuration, change, ticketing, exception, and evidence data. - Creating data quality, lineage, reconciliation, and completeness checks that make control data defensible for SOX and other audit use cases. - Designing automated evidence generation workflows that produce complete, accurate, and repeatable audit populations, exports, dashboards, and control artifacts. - Developing control monitoring logic to detect drift, missing evidence, stale access, direct system changes, overdue activity, and other control exceptions. - Partnering with Security, IT, Infrastructure, Engineering, Risk Management, and system owners to understand source systems, validate data, and improve automation reliability. - Translating technical system behavior, data flows, access models, and validation results into clear explanations for auditors, control owners, and technical stakeholders. We’re looking for someone with - Strong data engineering, analytics engineering, or software/data systems experience, including building reliable datasets, pipelines, queries, dashboards, or automated reporting workflows. - Hands-on SQL experience and proficiency with at least one scripting or programming language such as Python. - Experience working with enterprise system data, such as identity platforms, HR systems, ticketing systems, cloud environments, source control systems, SaaS applications, or audit/compliance tooling. - Strong understanding of data modeling, lineage, completeness, accuracy, reconciliation, validation, observability, and repeatability. - Ability to reason through messy source-system data, inconsistent identifiers, nested groups, stale records, missing owners, direct assignments, and downstream application drift. - Experience supporting security, IT controls, SOX, audit readiness, risk, compliance, or regulated technology environments. - Ability to explain technical systems, data flows, and control logic clearly to both engineering and audit stakeholders. - Strong ownership, judgment, and attention to detail in high-stakes, time-sensitive environments. Nice to have: - Experience with Entra ID, Workday, GitHub, Databricks, Salesforce, or similar platforms. - Experience with cloud infrastructure environments such as Azure, AWS, or GCP. You might thrive in this role if: - You like turning messy operational processes into clean, repeatable systems. - You enjoy working at the intersection of data, controls, engineering, and audit. - You can go deep technically, but also explain your work clearly to auditors and executives. - You care about evidence quality, data integrity, and defensible documentation. - You are energized by building automation that reduces manual effort and improves control reliability. - You can partner with engineers without slowing them down, while still maintaining a strong control standard. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
查看中文参考译文
关于团队 IT 与安全部门构建系统、数据基础和自动化,帮助 OpenAI 安全、可靠地规模化运营。我们在身份、访问、基础设施安全、企业系统和内部生产力等关键领域提供支持。 随着 OpenAI 的发展,审计就绪性和控制保障越来越依赖可靠的数据:准确的系统清单、访问群体、变更记录、配置状态、异常信号,以及直接从源系统生成的证据。我们的目标是超越手动证据收集,构建可扩展的数据产品、自动化验证和持续控制监控,使安全和 IT 控制变得可衡量、可重复且可辩护。 关于职位 我们正在寻找一名 IT Controls Data Engineer,构建支撑审计就绪性、IT 控制、证据自动化和持续控制监控的数据基础设施。 在此职位中,你将设计并维护 pipeline、数据集、模型、验证逻辑、仪表板和证据导出,使 IT 控制变得可衡量、可重复且可辩护。你将跨安全、IT、基础设施、工程、财务风险管理以及审计团队工作,将复杂的系统行为转化为可靠的 control data products。 这是一个技术构建者角色。理想的候选人在 data engineering 和 analytics engineering 方面扎实,能够熟练处理企业系统和安全系统数据,并能向技术和审计利益相关者清晰解释 data lineage、source-system behavior 和 control logic。 你将负责 - 为 IT 控制构建可靠的 data pipelines、模型和数据集,包括访问、身份、配置、变更、工单、异常和证据数据。 - 创建 data quality、lineage、reconciliation 和 completeness checks,使控制数据在 SOX 和其他审计用途中可辩护。 - 设计自动化证据生成工作流,生成完整、准确且可重复的审计群体、导出、仪表板和 control artifacts。 - 开发控制监控逻辑,以检测 drift、缺失证据、stale access、直接系统变更、逾期活动和其他控制异常。 - 与安全、IT、基础设施、工程、风险管理和系统所有者合作,理解源系统、验证数据并提高自动化可靠性。 - 将技术系统行为、数据流、访问模型和验证结果转化为对审计人员、控制所有者和技术利益相关者的清晰解释。 我们寻找的人 - 扎实的 data engineering、analytics engineering 或软件/数据系统经验,包括构建可靠的数据集、pipelines、queries、dashboards 或自动化报告工作流。 - 具备实操 SQL 经验,并熟练掌握至少一种脚本或编程语言,如 Python。 - 有处理企业系统数据的经验,如 identity platforms、HR systems、ticketing systems、cloud environments、source control systems、SaaS applications 或 audit/compliance tooling。 - 对 data modeling、lineage、completeness、accuracy、reconciliation、validation、observability 和 repeatability 有深入理解。 - 能够推理混乱的 source-system data、inconsistent identifiers、nested groups、stale records、missing owners、direct assignments 和 downstream application drift。 - 有支持安全、IT controls、SOX、audit readiness、risk、compliance 或受监管技术环境的经验。 - 能够向工程和审计利益相关者清晰解释技术系统、数据流和控制逻辑。 - 在高风险、时间敏感的环境中具备强烈的 ownership、判断力和对细节的关注。 加分项: - 有 Entra ID、Workday、GitHub、Databricks、Salesforce 或类似平台的使用经验。 - 有 Azure、AWS 或 GCP 等 cloud infrastructure environments 的使用经验。 你可能适合这个职位,如果: - 你喜欢将混乱的运营流程转化为干净、可重复的系统。 - 你喜欢在数据、控制、工程和审计的交叉点工作。 - 你能够深入技术细节,但也能向审计人员和高管清晰解释你的工作。 - 你关注意据质量、数据完整性和可辩护的文档。 - 你对构建减少手动劳动、提高控制可靠性的自动化充满热情。 - 你能够与工程师合作而不拖慢他们的速度,同时保持强有力的控制标准。 如需通知 OpenAI 你认为此职位发布不合规,请通过此表单提交报告 https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA。与职位发布合规性无关的询问将不予回复。 在 OpenAI,我们相信人工智能有潜力帮助人们解决巨大的全球挑战,我们希望 AI 的收益能够被广泛分享。加入我们,共同塑造技术的未来。

译文仅供辅助阅读,具体要求以原始招聘来源为准。