Data Engineer Jobs in San Jose, CA

The role involves designing scalable data pipelines for 3D, video, and sensor data, optimizing infrastructure, and productionizing ML models with researchers.

The Design Data Integrity Engineer ensures the accuracy and compliance of engineering drawings and models, providing quality checks and support for manufacturability.

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 Lead Data Engineer will design, develop, and maintain ETL pipelines, ensuring effective data extraction, transformation, and loading from various sources, while collaborating with stakeholders and solving complex business issues.

The Data Engineer will support the development of autonomous driving technologies by creating algorithms, designing data pipelines, analyzing test data, and automating reports for decision-making.

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.

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

Design and implement data systems, manage projects, ensure data quality, mentor junior engineers, and collaborate with stakeholders.

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

Lead complex data engineering projects, develop data architectures, ensure data governance and compliance, and mentor the data engineering team.

Lead the design and implementation of complex data systems and architectures, ensuring data quality and mentoring junior engineers. Develop and maintain data pipelines, optimize data processes, and collaborate with cross-functional teams to meet business needs.

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.

The Principal Software Engineer will develop backend systems using Rust or Go, debug integrations, manage middleware components, and optimize data flows while following SDLC practices and collaborating with teams.

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.

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.

The role involves owning data science pipelines, delivering client-facing features, driving cross-functional collaboration, and leveraging AI tools to enhance workflows, ultimately transforming retail data into actionable insights.

As a Software Engineer on Glean's Data Foundations team, you'll build and scale data ingestion connectors, transforming unstructured content into structured data while ensuring system reliability and security throughout the data processing pipeline.

You will build scalable data pipelines for processing large datasets, optimize training throughput, and evolve data storage solutions at XPENG.

The role involves building and scaling data infrastructure for multimodal AI systems, developing high-throughput data pipelines, and collaborating with ML researchers and product teams to enhance data systems.

The Staff AI Engineer will design, implement, and maintain machine learning algorithms and systems, integrating AI components into applications and collaborating with cross-functional teams using cloud technologies and DevOps principles.

As a Senior Software Engineer, you will develop parallel algorithms for data processing, optimize C++ and CUDA code, and contribute to open-source projects.

Lead design and implementation of a scalable observability and data platform: build high-performance ingestion, governance and policy systems, unified web APIs/UX, tiered storage, and automation for lifecycle and pipeline orchestration to support NVIDIA engineers at scale.