223 results for Data Engineer Jobs in Mountain View, CA, US

Responsible for crafting data warehousing solutions, integrating open-source technologies, handling large data loads, designing warehouse tables and ETL pipelines, providing datasets for ML training, and building company-wide dashboards for tracking metrics.

Design, develop, test, deploy, and maintain production-grade data platforms and tooling. Ensure centralized data access, combine internal and external data sources via ETL/ELT tools, support ML teams, implement generative AI solutions, and manage projects with cross-functional stakeholders while adh...

Design and implement backend services and tools for data collection and processing related to autonomous vehicles. Develop smart labeling pipelines using deep learning, maintain monitoring for system metrics, and collaborate with various autonomous driving components to create evaluation metrics and...

About NewsBreakNewsBreak is redefining the way users interact with local news and their communities. By bridging local users, local content creators, and local businesses, our mission is to foster safer, more vibrant, and authentically connected lives. Through robust collaborations with thousands of...

Responsible for designing, developing, and optimizing data models, ETL pipelines, analytics workflows, and reporting dashboards. Collaborates with business teams to understand data needs and ensures data accuracy, consistency, and accessibility for strategic decision-making.

What To ExpectCome join a small team of experts building the Tesla's data platforms powered by all Tesla products (vehicles, solar panel, batteries, chargers, robots, autopilot, insurance, etc.).First Principles thinking is core of engineering culture at Tesla. Data is one of the key elements we use...

Design and automate infrastructure for processing data across multiple GPU clusters, work with researchers on data requirements, and optimize distributed loading for model training. Build infrastructure to manage large-scale datasets for model training.

Responsible for developing and managing a distributed data processing platform, focusing on data ingestion and processing, optimizing transport layer technologies like Kafka for real-time processing, and ensuring the data platform's availability and reliability.

Design and optimize scalable, cloud-native infrastructure for high-performance ML workloads. Develop and maintain efficient data ingestion pipelines and connectors for large-scale datasets. Build resilient ETL pipelines for data transformation and storage. Implement best practices for data security ...

As a foundational member of the Data Infrastructure team, responsible for productionizing the next generation of data tech stack, optimizing Apache Hudi's transactional engine, designing concurrency control and transactional capabilities, implementing indexing schemes, and solving optimization probl...