Data Engineer, CPU & Storage

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Through a combination of strategic partnerships and self-built campuses, we are scaling the compute, storage, and networking platforms that power frontier AI training and inference. The Scaling Analytics team builds the data and software systems that help Industrial Compute understand, plan, and operate infrastructure at global scale. We work across capacity, hardware, storage, infrastructure software, and operational systems to connect fragmented sources of infrastructure data and make that information reliable and usable for engineering and planning. As OpenAI's infrastructure footprint grows, CPU and storage data increasingly spans internal platforms, vendor systems, APIs, databases, object storage, capacity management systems, and operational tooling. Building reliable connections across these environments is critical to understanding available capacity, utilization, fleet state, and infrastructure growth. About the Role We are seeking a Data Engineer to build the data systems and integrations that connect OpenAI's CPU, storage, and supporting infrastructure platforms. This role sits at the intersection of data engineering and backend software engineering. Rather than focusing primarily on traditional analytical pipelines, you will build the software and integrations required to collect, normalize, and make infrastructure data available across a heterogeneous set of systems. CPU and storage data may originate from internal infrastructure platforms, vendor APIs, databases, object storage, capacity systems, and operational services. You will determine how to reliably connect these systems and where those integrations should live—whether within an existing infrastructure service, an orchestration framework, a scheduled workload, or a purpose-built application. You will work closely with Infrastructure Engineering, Capacity Engineering, Storage, Hardware Operations, and Infrastructure Software to create a reliable data foundation for understanding CPU and storage capacity, utilization, inventory, and operational state. Success in this role requires strong software engineering fundamentals, comfort working across unfamiliar systems, and the ability to design pragmatic solutions for moving and reconciling data across infrastructure environments. Responsibilities - Build integrations that collect CPU, storage, capacity, inventory, and operational data from internal systems and external vendors. - Connect data across APIs, databases, object storage, infrastructure services, and capacity management platforms. - Build backend services and scheduled workloads that normalize infrastructure data and make it available to engineering and analytics teams. - Design data models that create consistent representations of capacity, inventory, utilization, and infrastructure state across systems. - Determine the right architecture for new integrations, whether within existing services, orchestration frameworks, or purpose-built applications. - Build data-quality and reconciliation mechanisms to identify missing, stale, or inconsistent information across source systems. - Improve reliability through testing, monitoring, logging, and automated validation. - Develop reusable patterns for onboarding new infrastructure and vendor data sources as OpenAI's footprint grows Qualifications - Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. - 4+ years of experience in software engineering, data engineering, backend engineering, infrastructure engineering, or a related technical discipline. - Strong Python programming skills and experience building production software, services, automation, or data integrations. - Strong SQL skills and experience working directly with relational databases and large operational datasets. - Experience integrating systems through REST APIs, SDKs, databases, object storage, messaging systems, or other programmatic interfaces. - Experience building reliable batch, scheduled, or asynchronous workloads in production environments. - Strong understanding of software engineering fundamentals, including testing, debugging, version control, observability, and maintainable system design. - Experience reasoning about data schemas, system boundaries, data ownership, consistency, and failure modes across distributed systems. - Ability to navigate unfamiliar codebases and infrastructure environments and determine how new functionality should integrate with existing systems. - Experience partnering closely with infrastructure, backend, platform, or systems engineering teams. Preferred Skills - Experience working with compute, storage, capacity, fleet management, inventory, or hardware lifecycle data. - Strong backend engineering experience building services, APIs, integrations, a