Frontier AI Research · San Francisco
About the Team
OpenAI, in close collaboration with our capital partners, is building the world's most advanced AI infrastructure ecosystem. The Scaling Analytics team serves as the data backbone for this effort, enabling leaders and operators to make informed decisions across infrastructure deployment, hardware operations, supply chain, capacity planning, and site execution.
As OpenAI’s Industrial Compute expands across an increasing number of global data center campuses, the complexity of managing infrastructure capacity, hardware health, supply flows, and operational performance continues to grow. Scaling Analytics develops the data models, pipelines, metrics, and reporting systems that transform fragmented operational data into actionable insights, helping OpenAI operate infrastructure at unprecedented scale.
About the Role
We are seeking a Data Engineer to help build and scale the analytical foundations that power OpenAI's infrastructure organization. This individual will partner closely with Hardware Operations, Capacity Planning, Supply Chain, Infrastructure Delivery, Finance, and Engineering teams to create reliable data products that support critical operational and strategic decisions.
Today, much of the team's expertise is concentrated within several highly specialized domains including hardware health, GPU attribution, and supply analytics. As Stargate grows and new sites come online, the demand for analytics support continues to expand across both existing and emerging problem spaces. This role will increase the team's ability to move quickly, reduce operational bottlenecks, and provide additional depth across critical infrastructure analytics functions.
The ideal candidate combines strong data engineering fundamentals with an ability to navigate ambiguous operational environments, translating complex infrastructure problems into scalable data solutions that improve visibility, decision-making, and execution.
Key Responsibilities
Design, build, and maintain scalable data pipelines supporting infrastructure deployment, operations, capacity planning, and supply chain functions.
Develop trusted datasets and reporting systems that provide visibility into hardware inventory, deployment status, site readiness, capacity utilization, and operational performance.
Partner with cross-functional stakeholders to define metrics, establish data standards, and improve decision-making across infrastructure organizations.
Create scalable data models that enable consistent reporting and analytics across multiple data sources and operational systems.
Improve data quality, lineage, observability, and governance practices across critical infrastructure datasets.
Support executive reporting, operational reviews, forecasting exercises, and strategic planning initiatives through reliable analytical foundations.
Collaborate with engineering teams to integrate new data sources and operational telemetry into existing analytics ecosystems.
Build solutions that reduce manual reporting efforts and improve the speed and accuracy of infrastructure decision-making.
Document systems, processes, and analytical frameworks to improve long-term maintainability and organizational resilience.
Qualifications
5+ years of experience building and maintaining production data pipelines and analytical systems.
Strong proficiency in SQL and experience designing scalable data models.
Proficiency in Python or another programming language commonly used for data engineering.
Experience working with modern data warehouses (e.g., Snowflake, BigQuery, Redshift) and orchestration frameworks (e.g., Airflow, Dagster).
Experience designing reliable ETL/ELT workflows with a focus on maintainability, performance, and operational excellence.
Experience partnering with cross-functional stakeholders to translate business requirements into technical solutions.
Experience implementing data quality checks, monitoring, and observability practices in production environments.
Preferred Skills
Experience supporting infrastructure, hardware operations, supply chain, manufacturing, logistics, or capacity planning organizations.
Familiarity with large-scale operational telemetry and business-critical reporting environments.
Experience with distributed processing frameworks such as Spark.
Experience with transformation frameworks such as dbt.
Experience developing executive reporting and operational review metrics.
Experience operating in fast-paced, ambiguous environments with evolving priorities.
Interest in building the analytical foundations that support some of the world's largest AI infrastructure deployments.
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.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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