Data Engineer

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.

You will:

• Translate business requirements into conceptual, logical, and physical data models. 
• Define core data concepts for Waymo commercialization and implement models in the database.
• Design, build, and maintain data warehouse and pipeline solutions. Bring in and transform raw data that can be easily used to generate reports and insights for Waymo’s commercialization tracking and optimization.
• Ensure proper handling of PII and ACL. Implement a data quality framework, and maintain documentation. 
• Be highly collaborative and work closely with data producers and data consumers across Waymo to understand the data needs, provide consultation, and align data solutions.

You have:

• 6+ years of professional experience in data engineering or a related field
• Proven track record of building complex data engineering projects architectures from conception to deployment
• Experiences of designing and implementing data warehousing or data lake solutions like Google BigQuery and Snowflake, optimizing them for complex analytical queries and reporting
• Deep knowledge of relational and NoSQL databases
• Expertise in designing and implementing scalable data models, data quality frameworks, and data governance practices
• Proficient in SQL. Familiar with at least one of languages in Python, C++, or Java

We prefer:

• Familiarity with distributed processing frameworks and tools like Spark, Hadoop, or Kafka, handling massive datasets for real-time or batch analytics
• Deep understanding of data privacy, security, quality, correctness, and efficiency tradeoffs
• Proven track record of driving collaboration effectively across organizational boundaries, building multi-dimensional stakeholder relationships, and importing and exporting ideas to achieve broad organizational goals
• Experience in leading projects and driving collaborating with cross-functional teams.