Data Engineer Jobs in Sunnyvale, CA

The role involves analyzing and responding to email threats, developing detection technologies, and collaborating with global teams to mitigate spam and malware attacks. It requires strong problem-solving skills and some technical experience in relation to email security and data science.

The Staff, Data Center Augmentation Engineer will lead engineering efforts to upgrade data center infrastructure for AI workloads, focusing on power and cooling enhancements and managing complex retrofits.

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

Design, deploy, and manage data center networks for AI infrastructure. Troubleshoot issues, guide junior staff, and collaborate across teams.

Develop and maintain scalable data systems for sensor data, including ETL pipelines, hardware/software integration, and workflow collaboration.

The Data Engineer will manage the full data stack, design database architecture, build ETL pipelines, create data integrations, and oversee reporting and data quality.

As a Data Engineer, you will design database architecture, manage ETL/ELT pipelines, create financial reporting systems, and ensure data quality in collaboration with finance teams.

As a Full-Stack Engineer at Labelbox, you will develop and maintain AI tools, focusing on data training systems, intermediate user interfaces, scalable architectures, and work in a collaborative, fast-paced environment.

The Senior Software Engineer will design and implement cloud and vehicle data systems, enhancing offline data workflows, and collaborating with cross-functional teams.

Design and build scalable backend services for a trading platform, focusing on data ingestion, processing pipelines, and APIs while ensuring system reliability and integrating with various teams.

As a Data & Integration Engineer, you'll design and build integrations for ERP and CRM systems, ensuring reliable data flows and collaboration with cross-functional teams.

As a Software Engineer, you will enhance the data infrastructure by building new concurrency controls, indexing schemes, and optimizing distributed data processing algorithms.

Lead the design and optimization of data infrastructure, focusing on scalability. Requires expertise in GCP, ETL/ELT processes, and collaboration across teams.

The Data Infrastructure Engineer will analyze large datasets for edge cases in autonomous driving, collaborating with Machine Learning Engineers to improve safety and comfort.

As a Data Science and Machine Learning Software Engineer at NetApp, you will develop algorithms for real-time personalized search and recommendation using IoT data, while working on cloud-based services and analytics.

As a Staff Data Engineer, you will build and manage data ETL/ELT systems, ensure data quality and observability, optimize systems for performance, and collaborate with cross-functional teams.

As a Software Engineer 2 - Data Acquisition, you'll design and build data ingestion pipelines, ensuring quality and performance across multiple data domains while participating in code reviews and collaborating with data consumers.

Lead the design and development of scalable data acquisition systems, architect core components, and mentor engineers while collaborating across teams to fulfill data integration needs.

As a Principal Data Processing Engineer, you will enhance a data processing engine, collaborate on open-source platforms, and optimize performance.

Design and enhance large-scale data pipelines for machine learning teams, ensuring high-quality dataset delivery and facilitating new model deployments.

Design and develop scalable data processing systems and pipelines, create storage solutions, and ensure data integrity through testing and monitoring.

Design and develop scalable data pipelines and storage systems for machine learning evaluation, and create tools for data annotation and monitoring.

The Senior Data Analysis Engineer will analyze autonomous driving product performance, improve testing efficiency, automate metric generation, and collaborate with engineering teams to enhance product quality and insights.

Lead architecture and implementation of scalable ML data pipelines and tooling to turn autonomy data into training datasets. Build data selection, active learning, inference-at-scale, vector DB management, labeling integration, QC automation, and introspection tools while partnering with ML researchers and infra teams.

As a Staff Data Engineer, you will design and build large-scale data processing systems, ensuring data integrity and reliability while collaborating with cross-functional teams to influence architecture and technical roadmap.