Data Engineer Jobs in Santa Clara, CA

As a Senior Data Engineer, you'll design scalable data models, manage cloud pipelines using Google Cloud services, and optimize data architecture while collaborating with cross-functional teams.

The Data Engineer designs and manages data pipelines for lead generation, collaborates with Sales, analyzes metrics, and ensures data quality and integrity.

The Data Engineer will design, develop, and maintain scalable data systems, focusing on AWS and big data technologies to support data-driven decision-making and ensure data security.

As a Senior Data Engineer, you will define and own data pipelines, design schemas, partner with scientists, and improve data infrastructure for Merge Labs' molecular optimization platform.

As a Software Engineer III at GlossGenius, you will lead data engineering efforts, designing and implementing data models and pipelines while mentoring engineers and shaping the data platform's vision.

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.

As a Senior Staff Engineer, Data, you'll lead the design and implementation of FloQast's core data platform, ensuring scalability and reliability. You'll define standards for data ingestion and governance while collaborating with multiple teams and mentoring engineers.

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

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

Develop and automate data pipelines for ML systems, improve metrics dashboards, collaborate across teams, and support AI infrastructure development.

The Systems Engineer will develop data processing workflows, scientific algorithms, and analysis tools, focusing on measurement systems using Python and statistical methods, while collaborating in an Agile environment.

The Data Reliability Engineer will enhance the resilience and scalability of data infrastructure, focusing on automation and reliability. Responsibilities include managing data pipelines, operating Kubernetes clusters, and defining observability standards.

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.

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.