Lead Data Platform Engineer - Enterprise, Data & AI
At a glance
Senior Data Engineering role at Zoox. Foster City · full-time · $230,000–$277,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Build data pipelines that adjust to schema changes, flag anomalies, stop unsafe flows and recover from failures automatically
- Set rules for data access, quality checks, schema changes and metadata so teams can rely on governed data
- Tune storage, compute and queries to control costs while keeping data access fast for analytics and AI agents
- Create deployment templates, isolated test environments and version controls for reliable data releases without downtime
What you bring
- At least ten years of hands-on data platform or software engineering, including scaling production data foundations
- Strong experience tuning queries and allocating compute, with a track record of reducing infrastructure costs
- Practical background with enterprise access controls, data masking and compliance needs such as audits and retention
- Experience setting governance and data quality controls, plus building automated CI/CD and deployment testing
Who this fits
This is a hands-on technical lead role for someone who wants to build and own large-scale data infrastructure. The position is hybrid in Foster City, California.
From the employer
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.
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AccommodationsIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com 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.
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