Data Engineer Jobs in Santa Clara, CA

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.

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.

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.

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.

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 Big Data Developer (Spark) will be responsible for Spark and Scala development, Hadoop performance tuning, and SQL coding. Requires extensive experience in data processing and performance optimization.

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.

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

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.

The Principal Engineer will lead the architecture and implementation of AI-powered systems for data analytics, collaborating with teams to create closed-loop systems and driving engineering excellence while measuring business outcomes.

The role involves designing and building data pipelines for analyzing user feedback on AI models, ensuring data quality and infrastructure scalability.

Responsible for managing partnerships with strategic ISVs to drive adoption of NVIDIA's technology stack, ensuring integration and alignment with business goals. Lead cross-functional teams for successful collaboration and product strategy.

As a Research Engineer, you conduct pioneering research in autonomous systems and develop models using large-scale data and advanced simulators, collaborating with scientists and contributing to high-quality publications.