Data Engineer, CPU & Storage

Compensation

$293K – $385K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
• 401(k) retirement plan with employer match
• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
• Mental health and wellness support
• Employer-paid basic life and disability coverage
• Annual learning and development stipend to fuel your professional growth
• Daily meals in our offices, and meal delivery credits as eligible
• Relocation support for eligible employees
• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

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.

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.

Responsibilities

• Build and maintain software integrations that collect CPU, storage, capacity, inventory, and operational data from internal systems and external vendors.
• Connect heterogeneous data sources including APIs, relational databases, object storage, infrastructure services, capacity management platforms, and vendor systems.
• Design reliable ingestion mechanisms for both structured and semi-structured infrastructure data, including batch, scheduled, and API-driven workflows.
• Determine the appropriate architecture and execution environment for new data integrations, including existing backend services, capacity systems, orchestration frameworks, scheduled workloads, or purpose-built services.
• Build backend services, jobs, and tooling that normalize infrastructure data and make it available through databases, offline tables, and analytical datasets.
• Develop reliable interfaces between operational systems and downstream analytics, planning, and engineering workflows.
• Partner with infrastructure and software engineering teams to understand source systems, APIs, data ownership, schemas, and operational constraints.
• Design data models that reconcile information across multiple systems and establish consistent representations of CPU capacity, storage capacity, inventory, utilization, and infrastructure state.
• Build mechanisms for detecting missing, stale, inconsistent, or incorrect infrastructure data and resolving discrepancies between source systems.
• Improve the reliability, observability, and maintainability of data integrations through testing, monitoring, logging, and automated validation.
• Support infrastructure planning and operational analysis by ensuring critical CPU and storage datasets are accurate, timely, and accessible.
• Develop reusable patterns for onboarding new infrastructure and vendor data sources as OpenAI's compute footprint and partner ecosystem expand.

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 building backend or data systems that integrate information across multiple internal services, databases, APIs, and external platforms.
• Experience working with infrastructure capacity, compute, storage, fleet management, inventory, or hardware lifecycle data.
• Familiarity with CPU platforms, storage systems, distributed systems, cloud infrastructure, or large-scale hardware environments.
• Experience building integrations with third-party or vendor APIs where schemas, interfaces, data quality, and availability may vary across providers.
• Experience working with workflow orchestration or scheduling systems such as Airflow or comparable frameworks, while understanding when orchestration is appropriate versus building functionality into an existing service.
• Experience with relational databases, object storage, offline tables, and analytical data systems, with the ability to move comfortably between operational and analytical environments.
• Experience designing reconciliation and data-quality mechanisms across systems that may contain overlapping or conflicting representations of infrastructure state.
• Strong backend engineering instincts, including API design, service integration, reliability, observability, and production debugging.
• Ability to evaluate multiple implementation approaches and choose pragmatic architectures based on reliability, maintainability, ownership, and operational complexity.
• Experience working in large-scale cloud, hyperscale infrastructure, AI infrastructure, or similarly complex distributed environments.