Guide consultations with cross-organizational partners to define data sources and validation standards, partnering with engineers and data scientists on ML training. Oversee the development of infrastructure and business solutions to scale common frameworks, and design secure data processing systems while advocating for best practices. Direct the development and scaling of data models, pipelines, and exchange formats to reduce data fragmentation and increase data discoverability.
Leverage , deploy, and continuously train ML models while implementing new storage and serving systems to scale across Data Engineering. Manage data profiling and analysis using existing data models and custom infrastructure to clarify client requirements and enable data-driven decision-making.
Job description provided by Google.
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