Lead Data Platform Engineer - Enterprise, Data & AI

The role

You will build and scale self-healing data pipelines that handle schema changes, detect anomalies and recover from failures. You will also set company-wide data governance and quality rules, and optimize storage, compute and query performance for analytics and AI agents.

What you will do

• Scale self-healing data pipelines that handle schema evolution, detect anomalies, run circuit breakers and recover from failures.
• Define and enforce company-wide data governance, access, automated data quality testing, schema evolution policies and metadata management.
• Implement storage lifecycle strategies, resource throttling and query optimization for high-throughput, low-latency data access for analytics and AI agents.
• Optimize cloud cost and performance, with a focus on Databricks vs EMR (AWS).
• Build automated CI/CD deployment templates, environment isolation, testing frameworks and version control standards for zero-downtime deployments.

Required qualifications

• 10+ years of hands-on experience in Data Platform Engineering or Software Engineering.
• Track record of architecting and scaling production-grade data foundations.
• Deep expertise in scaling and optimization, query tuning and compute resource allocation.
• Experience implementing 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.
• Familiarity supporting enterprise compliance requirements such as SOX, audit trail controls and data retention policies.
• Experience 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, version control and automated deployment testing for data assets.

Nice to have

• Experience incorporating LLMs or GenAI into pipeline operations, such as code generation, root-cause analysis, data reconciliation, backfills or anomaly detection.
• Experience with infrastructure-as-code (Terraform) and containerization/orchestration (EKS) for elastic compute management.
• GPU/CPU performance optimization and utilization.
• Previous experience in the autonomous vehicle, robotics or high-tech manufacturing sectors.

Before you apply

• You do not need to match every listed expectation to apply.

About the company

Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem to bring this technology to market. It aims to provide next-generation mobility-as-a-service in urban environments.