Data Engineer Jobs in Santa Clara, CA

Lead the design and development of scalable data acquisition systems, architect core platform components, provide mentorship, and ensure best practices in software engineering.

Design, develop, and maintain AI/ML platform infrastructure ensuring scalability and reliability. Collaborate across teams, drive technical direction, and own components.

Design, develop and implement software features for Prisma Access, focusing on scalability and cloud-native deployment while collaborating with various teams.

As a Staff Data Engineer, you will create and maintain data pipelines, design ETL processes, and mentor engineers to enhance advertising products through data-driven insights.

Transform raw data into trusted datasets; build and optimize data pipelines; integrate customer data; ensure data quality and reliability.

The Senior Data Engineer will develop and manage data infrastructure and pipelines, collaborating with the ML team to support analytics and machine learning applications.

Design and develop core data infrastructure for AI platform, focusing on scalable systems, database architecture, and high-throughput data management, enabling efficient data streaming for model training.

Design and develop data visualization tools for AI performance, collaborate with engineers, define visualization standards, and drive user experience innovation.

The Staff Engineer will design and build scalable Data Lakehouse components, lead architecture sessions, innovate with open-source tools, and mentor other engineers.

As an Engineer II, you will design and build scalable components for a Data Lakehouse, lead architecture sessions, innovate with new tools, and ensure system quality and performance while collaborating across teams.

The Senior Software Engineer will scale open-source data infrastructure, handle data lifecycle tasks, and support internal and external products.

As a Senior Staff Data Engineer, you'll design and develop scalable data platforms, mentor engineers, and ensure compliance while enhancing the developer experience for data scientists and ML engineers.

Design and implement evaluation pipelines for AI models, focusing on user feedback integration and performance optimization in consumer products.

As a Software Engineer on the Data Analytics team, you will build analytics infrastructure, improve data quality, mentor juniors, and support data tools for various teams.

As a Senior Data Analytics and AI Engineer, you'll lead data analytics, build data pipelines, collaborate with teams, and mentor junior engineers in DFT methodology.

Lead the architecture, design, and implementation of a high-performance data processing engine focused on large-scale data processing.

As a Data Engineer, you will design and optimize data models, ETL pipelines, and analytics workflows to support data-driven decision-making for business stakeholders.

Design and develop data solutions, optimize ETL/ELT pipelines, integrate ML models, collaborate with engineers, and operationalize analytics for semiconductor R&D and operations.

The Data Operations Engineer will optimize and maintain data labeling workflows, automate tasks, and ensure quality in data annotation processes.

The Senior Software Engineer will design and maintain systems for efficient data transfer to facilitate NVIDIA's AI workflows, focusing on distributed systems and protocols.

As a Software Engineer on the Data Platform team, you will design, build, and optimize distributed systems for high-throughput data processing, collaborating with diverse teams to enhance data workflows.

The role involves designing and implementing data ingestion pipelines, developing components for data transformation, improving platform observability, and collaborating with data consumers.

Develop and implement features in VLM data infrastructure, collaborate with ML teams to address issues in data processing, and design scalable solutions for model improvement.

The role involves designing and implementing data acquisition and processing pipelines, improving data quality, and enhancing data pipeline infrastructure in robotics at Google Deepmind.

The role involves building data strategies, collaborating on model evolution, and designing data storage systems to enhance foundation model training for autonomous driving.