Technical Product Manager, Data Infrastructure

Lightwheel; Mountain View (CA); On-site; USD 170,000 - 210,000; Full time

Job summary

Lightwheel is seeking a Technical Product Manager, Data Infrastructure to own strategic customer data deliveries and help scale the Data Delivery Platform into reusable infrastructure. You will define data schemas, validation, adapters, and APIs, while ensuring observability and cost optimization.

Responsibilities include translating customer requirements into technical specs, driving end-to-end delivery, and scaling operations to support large data-hour programs, with a focus on

Qualifications

• 3+ years in software engineering or data infra.
• Hands-on with Python, APIs/SDKs, AWS/GCP, Kubernetes, and data pipelines.
• Experience building or operating production data platforms or large-scale data pipelines.
• Strong problem-solving across compute, storage, network, and APIs.
• Experience working directly with technical customers and leading cross-functional projects.
• Fluent in English and Mandarin.

Responsibilities

• Own Data Platform - Define and evolve data schemas, validation, adapters, conversion, cloud transfer, APIs/SDKs, observability, and cost optimization.
• Drive Customer Delivery - Translate customer requirements into technical specs, acceptance criteria, and delivery plans; own programs end-to-end through customer acceptance.
• Scale Data Operations - Build systems and processes capable of supporting 100K-1M+ data-hour programs with predictable throughput, reliability, and cost.
• Solve Complex Technical Problems - Identify and resolve bottlenecks across compute, storage, networking, data pipelines, APIs, and customer ingestion.
• Build Scalable Processes - Standardize delivery workflows, quality gates, versioning, and change management to make customer onboarding repeatable and scalable.
• Lead Cross-Functional Execution - Work closely with Engineering, Data Operations, Infrastructure, and customers to drive technical delivery and continuously improve the platform.

Skills

3+ yrs exp

Python

APIs/SDKs

AWS/GCP

Kubernetes

Data pipelines

English & Mandarin

Tools

AWS

GCP

Kubernetes

Job description

About the Role

We are looking for a Technical Product Manager, Data Infrastructure to own strategic customer data deliveries and help build Lightwheel's Data Delivery Platform into scalable, reusable infrastructure.

Responsibilities

• Own Data Platform - Define and evolve data schemas, validation, adapters, conversion, cloud transfer, APIs/SDKs, observability, and cost optimization.

• Drive Customer Delivery - Translate customer requirements into technical specifications, acceptance criteria, and delivery plans; own programs end-to-end through customer acceptance.

• Scale Data Operations - Build systems and processes capable of supporting 100K-1M+ data-hour programs with predictable throughput, reliability, and cost.

• Solve Complex Technical Problems - Identify and resolve bottlenecks across compute, storage, networking, data pipelines, APIs, and customer ingestion.

• Build Scalable Processes - Standardize delivery workflows, quality gates, versioning, and change management to make customer onboarding repeatable and scalable.

• Lead Cross-Functional Execution - Work closely with Engineering, Data Operations, Infrastructure, and customers to drive technical delivery and continuously improve the platform.

Qualifications

• 3+ years of experience in software engineering, data infrastructure, distributed systems, ML/robotics infrastructure, or customer engineering.

• Strong hands-on engineering background with Python, APIs/SDKs, AWS/GCP, Kubernetes, and data pipelines.

• Experience building or operating production data platforms or large-scale data pipelines.

• Strong problem-solving skills with the ability to diagnose bottlenecks across compute, storage, network, and APIs.

• Experience working directly with technical customers and leading cross-functional projects.

• Fluent in English and Mandarin.

Preferred Qualifications

• Experience in robotics, autonomous driving, embodied AI, or Physical AI.

• Experience with large-scale video, sensor, multimodal, or ML training datasets.

• Familiarity with LeRobot, MCAP, ROS bags, TB/PB-scale data, or cloud data transfer.

• Experience in forward-deployed engineering, enterprise data integration, or building infrastructure functions from the ground up.