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.
This role follows a hybrid work schedule and reports to Sr. Staff TLM.
You will:- Lead, mentor, and grow a team of data engineers responsible for the Waymo Commercialization Data Lake and associated data pipelines.
- Define and drive the technical vision, strategy, and roadmap for the Data Engineering team, aligning with Waymo's goals.
- Oversee the design, development, and operation of scalable and reliable data pipelines, data stores, and data models to ingest, process, and serve commercialization data.
- Establish and enforce best practices for data quality, governance, security, and performance optimization within the data ecosystem.
- Collaborate closely with Product Data Scientists, Engineering, and Operations teams to understand data needs, define requirements, and deliver robust data solutions.
- Foster a culture of engineering excellence, innovation, and continuous improvement within the team.
- BS/MS/PhD in Computer Science or a related field.
- 7+ years of experience in data engineering, software engineering, or a related role, with a focus on large-scale data systems.
- Proven experience (2+ years) in managing and leading engineering teams, including hiring, coaching, and performance management.
- Demonstrated technical leadership in designing, architecting, and delivering complex, large-scale data systems and pipelines, including setting technical direction, making key design trade-offs, and mentoring other engineers.
- Strong understanding of data warehousing concepts, data modeling, and ETL/ELT processes.
- Expertise in SQL and proficiency in at least one programming language such as Python, Java, or C++.
- Experience building and scaling data lakes or large-scale data platforms.
- Expertise with big data technologies and distributed systems (e.g., Spark, Flume, Kafka, BigQuery, etc.).
- Knowledge of data governance, data quality frameworks, and data security best practices.
- Experience working in a fast-paced, product-driven environment.
- Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
- Domain knowledge in ride-hailing, mobility, or autonomous vehicles.
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
Waymo Mountain View, California, USA Office
1600 Amphitheatre Pkwy, Mountain View, CA, United States, 94043
Similar Jobs
.jpeg)
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
