About The Role

Join Waymo as a Tech Lead Manager (Data Engineer) and lead a team of data engineers responsible for the Waymo Commercialization Data Lake and associated data pipelines. You will define and drive the technical vision, strategy, and roadmap for the Data Engineering team, oversee the design and development of scalable data pipelines, and collaborate closely with cross-functional teams. This role offers a hybrid work schedule and a comprehensive benefits package.

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.
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
BS/MS/PhD in Computer Science or a related field
Expertise in SQL and proficiency in at least one programming language such as Python, Java, or C++
7+ years of experience in data engineering, software engineering, or a related role, with a focus on large-scale data systems
Strong understanding of data warehousing concepts, data modeling, and ETL/ELT processes
Domain knowledge in ride-hailing, mobility, or autonomous vehicles
Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams
Experience working in a fast-paced, product-driven environment
Knowledge of data governance, data quality frameworks, and data security best practices
Expertise with big data technologies and distributed systems (e.g., Spark, Flume, Kafka, BigQuery, etc.)
Experience building and scaling data lakes or large-scale data platforms

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