Tech Lead Manager; Data Engineer

Requirements

• 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++
• (Desirable) Experience building and scaling data lakes or large-scale data platforms
• (Desirable) Expertise with big data technologies and distributed systems (e.g., Spark, Flume, Kafka, Big Query, etc.)
• (Desirable) Knowledge of data governance, data quality frameworks, and data security best practices
• (Desirable) Experience working in a fast-paced, product-driven environment
• (Desirable) Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams
• (Desirable) Domain knowledge in ride-hailing, mobility, or autonomous vehicles

• This role follows a hybrid work schedule and reports to Sr. Staff TLM
• 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