Technical Lead Manager, Query & Storage SWE

Location: Mountain View, CA

Department: CSI (7LV)

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

You will:

• Lead, mentor, and grow a team of software engineers, fostering a culture of engineering excellence, innovation, and collaboration.
• Define and execute the technical roadmap of the data pipeline, storage, and query infrastructure for Waymo driver evolution and commercialization expansion
• Drive the design, development, and operation of highly scalable, reliable, and efficient distributed systems for massive-scale data processing and analysis.
• Collaborate closely with stakeholders across Engineering (e.g., Perception, Planner, Simulation) and Data Science to understand needs and deliver impactful solutions.
• Own the end-to-end lifecycle of your team's systems, including architecture, implementation, testing, deployment, and monitoring.
• Champion best practices in software development, system design, and operational excellence.

You have:

• BS, MS, or PhD in Computer Science or a related field.
• 8+ years of software engineering experience, with a proven track record of designing and building large-scale distributed systems.
• Deep understanding of query engines and query optimization (e.g., F1 Query, Presto) and storage systems (e.g., Bigtable, Spanner).
• 2+ years of experience in engineering management or tech leadership, including people management, project leadership, and technical direction.
• Strong software development skills, with proficiency in SQL and one of C++/Java/Python.
• Excellent problem-solving, communication, and interpersonal skills.

We prefer:

• Demonstrated ability to influence and drive alignment across multiple teams.
• Experience with data warehousing, data modeling, and SQL optimization.
• Expeience with data processing frameworks (e.g., Flume, Spark, Beam) and stream and batch processing technologies.
• Familiarity with Google's internal data infrastructure and tools.
• Domain knowledge in autonomous vehicles, robotics, or large-scale data analysis.