Data Engineer, Hardware & Consumer Devices

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About the role

About the team OpenAI is building a new generation of AI-powered consumer devices, creating opportunities to bring increasingly capable AI into people's everyday lives. Our Data Engineering team is responsible for establishing the foundational data infrastructure that supports the development, manufacturing, launch, and ongoing operation of these products. We're building the systems that connect information across the entire device lifecycle, enabling engineering, operations, and Data Science partners to understand product performance, identify problems, and make better decisions. This is an early-stage organization with significant greenfield opportunities. We're looking for engineers who want to shape the technical foundations of a rapidly growing business and establish systems that will scale alongside our products. About the role: As a Data Engineer, you'll design, build, and scale the data infrastructure that powers OpenAI's hardware and consumer devices organization. You'll tackle technically challenging problems involving complex data sources, evolving operational requirements, and systems that need to scale from early development through manufacturing and consumer deployment. Unlike roles focused primarily on supporting individual analytics projects, this position emphasizes building durable, reusable data foundations that enable multiple teams and use cases. You'll have significant ownership over technical decisions, work closely with partners across engineering, manufacturing, operations, and Data Science, and help define how we approach Data Engineering as the organization grows. In this role, you will: - Build foundational data infrastructure: Design and implement reliable, scalable data pipelines, platforms, and datasets that support hardware development, manufacturing, customer operations, and device performance. - Connect complex data ecosystems: Integrate information across manufacturing systems, factory operations, device telemetry, quality assurance, and customer-facing operational systems. - Establish durable data models: Develop reusable datasets and data architectures that enable consistent measurement, investigation, and decision-making across multiple teams. - Enable manufacturing and quality intelligence: Connect manufacturing conditions and production history with downstream product performance, reliability, returns, and failure signals. - Prepare for scale: Design systems that evolve from early-stage development and initial production to increasingly complex operations and large-scale consumer deployment. - Partner across disciplines: Work with hardware and software engineers, manufacturing teams, operations leaders, and Data Scientists to translate emerging requirements into robust technical solutions. - Shape our technical direction: Help establish engineering standards, architectural principles, data quality practices, and infrastructure decisions that will influence the organization for years to come. You might thriv...

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