Tech Lead Manager, Data Engineer

Job Summary

The role involves leading, mentoring, and growing a team of data engineers responsible for the Waymo Commercialization Data Lake and associated data pipelines.

Responsibilities

• 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.

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++.
• 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.

Qualifications

• 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.

Skills

• Data Engineering
• Data Modeling
• ETL/ELT Processes
• SQL
• Programming Languages (Python, Java, C++)
• Data Governance
• Data Quality Frameworks
• Data Security Best Practices
• Data Warehousing Concepts
• Big Data Technologies
• Distributed Systems (Spark, Flume, Kafka, BigQuery)

Benefits

Discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Pay

The expected base salary range for this full-time position across US locations is $251,000—$310,000 USD.

Schedule

This role follows a hybrid work schedule.