The Principal Engineer for Data Quality at Google will lead the technical direction and strategy for the Data Quality team within the AI Foundry. This team is responsible for delivering high-quality datasets that enhance the user experience across various Google products, including Search and DeepMind. The role involves collaborating with researchers and engineers to ensure data quality and establish self-healing data systems. This position offers a unique opportunity to influence how Google utilizes data at scale.

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related technical field.
• 15 years of experience in software engineering, building and working with systems in the technology organization.
• 7 years of experience in a technical leadership role with or without direct reports.
• 5 years of experience developing and deploying machine learning models on data sets.
• 3 years of experience in infrastructure or data systems, building or managing infrastructure products.

• Lead the strategy, technical vision, and roadmaps for the data quality team to deliver high-quality datasets for DeepMind and Search.
• Drive the architecture toward establishing the data flywheel for ML training data and Search Context that can self-correct and self-heal.
• Collaborate closely with DeepMind and Search researchers, data analysts, and engineers to identify key Value of Data signals.
• Partner with infrastructure owners in AI Foundry to evolve systems to deliver high-quality datasets that power Search features and AI models.
• Provide technical guidance to critical components of the context quality area, such as large-scale signal developments and design of quality metrics.

• Employees at Google are often offered benefits like comprehensive health insurance, 401(k) matching, and flexible work arrangements, among other benefits.