Tech Lead Manager, Data Engineer

About the role

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.

You have:

- 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++.

We prefer:

- 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.