Lead Data Platform Engineer - Enterprise, Data & AI Zoox - 2.9 Foster City, CA Job Details Full-time $230,000 - $277,000 a year 1 hour ago Benefits Disability insurance Health insurance RSU Paid time off Life insurance Qualifications Resource allocation AWS IAM Data integrity assurance Version control Cloud identity and access management (IAM) Performance tuning Software engineering Authorization controls implementation Software design Continuous Delivery (CD) implementation IT user and group management Data validation techniques Data Retention (Data management) Data retrieval time improvement Process design Application deployment Cost control SOX Schema design Information security compliance Reducing cloud infrastructure costs Data Architecture Design (Architecture design skills) Data quality monitoring Data access controls implementation Retention policy implementation Developing automated testing protocols Scalability Identity and access management (IAM) architecture design Storage management (system administration) Access control management Full Job Description Zoox is seeking a high-agency, hands-on Lead Data Platform Engineer to architect, optimize, scale and own the next generation of our enterprise & AI data foundation. In this role, you will architect a high throughput, data fabric that unifies data across Zoox and downstream AI agents. You will drive performance tuning, cost optimization, RBAC, data governance and CI/CD pipelines to deliver secure, low-latency, 'AI-ready' data foundations across the organization. You will serve as the primary technical driver for our data platform, designing autonomous frameworks, building scalable data infrastructure and establishing strict standards for security and developer velocity. This is an engineering-intensive leadership role for a builder who thrives on solving complex challenges. In This Role, You Will... Scaling self-healing data pipelines that automatically handle schema evolution, detect anomalies, execute circuit breakers and recover from failures without manual intervention. Define and enforce company-wide data governance, access, automated data quality testing, schema evolution policies and metadata management to maintain high-fidelity data assets. Implement intelligent storage lifecycle strategies, resource throttling and query optimization to minimize compute overhead while delivering high-throughput, low-latency data access for analytics and AI agents. With a focus on Databricks vs EMR (AWS) cloud optimization (cost and performance). Build automated CI/CD deployment templates, environment isolation, testing frameworks and version control standards, enabling rapid, reliable and zero-downtime deployments Qualifications 10+ years of hands-on experience in Data Platform Engineering or Software Engineering with a proven track record of architecting and scaling production-grade data foundations. Deep expertise in scaling and optimization, query tuning, compute resource allocation and implementing efficient compute-storage lifecycle policies to minimize infrastructure costs. Experience implementing enterprise security standards, Role-Based Access Control (RBAC), Active Directory/IAM roles and fine-grained data masking, with strong familiarity supporting enterprise compliance requirements (e.g., SOX, audit trail controls, data retention policies). Track record of establishing enterprise data governance frameworks, automated schema evolution controls, data quality audits and near real-time observability/alerting. Hands-on experience building automated CI/CD pipelines, environment isolation (branch testing, rollback mechanisms), version control and automated deployment testing for data assets. Bonus Qualifications Experience incorporating LLMs or GenAI directly into pipeline operations (e.g., code generation, triage and root-cause analysis, automated data reconciliation, backfills or anomaly detection). Experience with infrastructure-as-code (Terraform) and containerization/orchestration (EKS) for elastic compute management. GPU/CPU performance optimization & utilization. Previous experience in the autonomous vehicle, robotics or high-tech manufacturing sectors. Base Salary Range There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position. Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance. About Zoox Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn Accommodations If you need an accommodation to participate in the application or interview process please reach out to or your assigned recruiter.

A Final Note:

You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.