Sr. Staff Data Architect

Waymo•Mountain View, CA

1d•$298,000 - $368,000

About The Position

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

Requirements

BS/MS/PhD in Computer Science, Computer Engineering, or equivalent.
12+ years of experience leading the design, implementation, and operations of multi-Petabyte Data Lake/Data Warehouse solutions in high-growth companies.
Proven track record of being the Lead Architect driving significant data governance and data platform maturity transitions (e.g., ad-hoc ➔ standardized).
Deep experience driving a data infrastructure org through rapid growing phrase, effectively balancing speed for analysts with central governance guardrails.
Expert-level technical depth in distributed batch/streaming frameworks (e.g., C++, Flume, Apache Spark, Flink).
Highly effective cross-functional influencer; capable of driving alignment across hundreds of Stakeholders (Director+ levels, Embedded Eng, Data Science).

Nice To Haves

Hands-on knowledge of cloud-native or internal release hardening ecosystems (e.g., Canary/CAS, CI/CD pipelines, container orchestration).
High proficiency with Google-internal pipeline/data stacks (Flume, SQLP, Rapid, CAS, F1).

Responsibilities

Define and drive the global architectural roadmap for Waymo's Data Lake, governing the transition from ad-hoc processing to a production-grade, highly scalable analytical ecosystem.
Serve as the ultimate Tech Lead (TL) over cross-domain data pipelines, governing dependencies and maintaining platform consistency across both centralized infrastructure and embedded product domains.
Champion and enforce linear DAG architectures and modern Lakehouse/Medallion standards to untangle highly coupled, opaque "spaghetti" lineage.
Chair centralized Data Design Review forums, establishing unified standards for modularized code, testing suite enforcement, DAG dependency registration, and environmentalization.
Architect common, self-service frameworks and "Managed Pipeline Services" (like hardened wrappers and templates) for downstream consumption by Data Engineers and Product Data Scientists.
Oversee core integration strategies for Data Governance, ensuring privacy (GDPR), access Control (IAM/RBAC), and pipeline compliance are deeply baked into core architecture.