Data Engineer Jobs in Santa Clara, CA

Design and develop scalable data infrastructure for AI platform, optimize database performance, create data pipelines, and mentor junior engineers while collaborating across teams.

Develop and maintain internal web-based tools for client telemetry and logging by collaborating with cross-functional teams and ensuring data integrity.

As a Senior Solutions Engineer, you will support customers in deploying ML applications, ensuring technical success, and enhancing their understanding of Flyte and Union Cloud.

Build and automate infrastructure for large-scale data processing, optimize distributed loading for model training, and manage datasets for model training.

The role involves designing and building resilient data processing infrastructure, optimizing systems for large-scale data operations, and collaborating with researchers on technical requirements.

Design and maintain scalable data pipelines, develop infrastructure for dataset reliability, implement benchmarking systems, and automate quality checks for ML models.

The role involves designing and developing scalable software features for Palo Alto Networks' Prisma Access, collaborating across teams to enhance software quality, and troubleshooting customer issues.

As a Staff Software Engineer on the Data Science team, you'll develop and scale data science tools and machine learning models for the company's marketing intelligence platform, ensuring reliability and performance in data-driven solutions.

As a Staff Software Engineer on the Data Science team at Northbeam, you'll design and implement data-driven solutions, scale data products, and develop machine learning models, directly impacting the company's core product.

As a Senior Data Engineer, you'll design and maintain scalable, secure SaaS products while collaborating on AI-powered healthcare solutions. Responsibilities include front-end and back-end development, API design, and ensuring code quality.

The Lead Data Engineer is responsible for designing, developing, and maintaining ETL pipelines to manage financial data, ensuring compliance and business intelligence.

The Staff Data Engineer will lead efforts in data warehousing, pipeline optimization, product analytics systems, and data quality improvement to support business growth.

The Lead Data Engineer will design and implement a modern data infrastructure for analytics and ML at Midi, leading cross-functional collaboration and developing data products.

The Senior Staff Engineer will architect and build a Data Lakehouse platform, optimize Spark jobs, and mentor the engineering community at GEICO.

The Software Engineer will design and build large-scale data platforms, optimize data processing systems, and improve machine learning infrastructure for AI research.

The Senior Data Engineer will standardize and reuse data, develop features, create ETL processes, and collaborate with cross-functional teams.

Design and improve data pipelines, maintain data flows, apply ML techniques for data curation, and collaborate across teams.

Build and maintain foundational datasets for data-driven decision-making, creating scalable data pipelines and collaborating across teams to enhance data models and practices.

The Staff DataOps Engineer applies DevOps principles to data platforms, automating pipelines, leading initiatives to improve data system reliability and scalability, and mentoring teams.

As a Principal Engineer, you will lead the Data Infra team in building scalable data processing systems for millions of users while ensuring compliance with data regulations.

As a Senior Software Engineer, you'll drive the software development lifecycle, ensuring the delivery of innovative solutions for risk management and fraud detection, working with large-scale data and integration across APIs.

As a Senior Staff Software Engineer, you will architect data models and systems, ensuring data integrity and consistency for enterprise use, while collaborating with various teams.

As a Staff Data Lake Engineer, lead the development of an enterprise data platform, mentor junior engineers, and ensure technical execution in data architecture and strategy while collaborating across teams.

Design and implement data ingestion pipelines, develop reusable components, support observability, and partner with data consumers to enhance data integration.

Lead the design and development of scalable data acquisition systems, mentor engineers, and integrate diverse internal and external data sources. Architect platform components for high-volume data processing with a focus on reliability and governance.