About the job
About Our Team
At OpenAI, our Procurement Center of Excellence (COE) is dedicated to creating an AI-driven procurement analytics and reporting infrastructure. This initiative empowers our leaders and operators to make informed decisions based on reliable data while facilitating automation through clean, policy-compliant inputs. This pivotal role focuses on consolidating data across our procurement spectrum, overseeing definitions and governance, and transforming chaotic operational signals into sustainable self-service insights.
About the Position
We are on the lookout for a Procurement Data Strategy & Analytics Senior Manager who will design and manage our comprehensive procurement data foundation. This encompasses everything from master data governance to robust production pipelines and insightful dashboards, covering critical areas such as Procurement, Travel & Expenses (T&E), and Extended Workforce tools.
In this role, you will develop and sustain reliable procurement dashboards using meticulously curated datasets. Your work will convert spend, supplier, and cycle-time data into self-service insights that enhance decision-making, user experience, and compliance visibility, ultimately enabling automation and GPT-agent workflows.
This position is located in San Francisco, CA, and follows a hybrid work model requiring three days in the office each week. We also provide relocation assistance for new hires.
Key Responsibilities:
Collaborate with our Enterprise Systems & Platform Team to design a cohesive procurement data mart integrating systems like Zip, Oracle, Ironclad, VNDLY, Navan, Salesforce, and various analytics tools, enabling Procurement to function with real-time, trustworthy intelligence.
Work alongside our Enterprise Systems & Platform Team to develop production-grade datasets and pipelines (e.g., in Databricks or comparable platforms) featuring consistent join logic, normalized tables, and scalable data quality controls.
Oversee procurement master data and governance (including suppliers, categories, items, entities, and cost centers): establish and enforce schemas, validation logic, taxonomy alignment, and consistent definitions across systems.
Construct the procurement data layer that supports AI and automation by ensuring structured, validated datasets that facilitate GPT agents, workflow automation, anomaly detection, and intelligent routing throughout procurement operations.
Deliver dashboards and self-service reporting for Source-to-Contract, Procure-to-Pay, T&E, and Extended Workforce metrics. Examples of metrics include: