Data Engineer Jobs in San Jose, CA

The Data Engineer will design and implement data pipelines and models, optimize data storage strategies, and ensure data quality while collaborating with machine learning teams.

The Business Systems Engineer will enhance data center operations by managing asset lifecycle, automating infrastructure systems, and integrating workflows for efficiency.

The Senior Engineer will develop applications for data management, implement data platforms, and ensure data flow and security compliance.

The role involves building data infrastructure, developing data pipelines, and collaborating with teams to ensure data quality and performance.

The role involves designing high-performance backend systems, processing customer SQLs, mentoring teammates, and improving the development environment.

Design and implement scalable data pipelines for AI models and analytics, optimizing performance and collaborating with ML Engineers.

The Principal Software Engineer will design and implement core components of a new cloud-native platform, leading architecture for scalable, distributed systems, while collaborating and mentoring engineers.

Design, implement, and maintain scalable data pipelines and analytical solutions, optimizing performance and ensuring data quality while collaborating with stakeholders.

We are seeking an AI/ML Engineer responsible for developing and implementing machine learning models, conducting data analysis, and ensuring accurate model performance.

The Staff Data Architect will design and implement enterprise data architecture, govern data modeling standards, and lead data engineering efforts across the organization.

Design and implement software solutions for data management and ingestion across enterprise AI/ML systems. Build and maintain distributed systems, solve complex engineering problems, and collaborate with teams for efficient data management.

The Principal Product Manager will lead the strategy for data platforms, enhancing data accessibility and usability while coordinating with engineering teams to optimize operations and improve scalability for Adobe products.

The Staff Software Engineer will curate data, build ETL workflows, automate processes, and serve as a liaison between scientific and engineering teams to enhance research data management.

As a Data Infrastructure Engineer, you'll develop solutions for massive data orchestration, support ML deployment, and lead technical directions for the team.

The Data Engineer will architect and maintain a data warehouse, optimize ETL processes, ensure data governance, and collaborate with stakeholders for data-driven decision making.

As a Staff Business Intelligence Engineer, you will design and code ELT/ETL pipelines, develop dashboards, maintain data models, optimize query performance, and mentor team members.

Design and develop scalable software features for Prisma Access, collaborating with teams to ensure quality and optimizing systems software for cloud operations.

As a Software Engineer II, you'll design, build, and maintain data infrastructure and pipelines, optimize data processing systems, and collaborate across teams to ensure high-quality data accessibility and security.

Lead the architecture and development of data systems and services for F5 Distributed Cloud, focusing on data engineering, analytics, and AI solutions.

The Staff Software Engineer - Vehicle Data Management will work on scalable data frameworks, APIs, and optimize systems using cloud technologies while collaborating across teams.

The Data Pipeline Engineer will implement and maintain big data infrastructure, develop REST APIs, and perform statistical analysis within an Agile environment.

As a Marketing Science Associate Analyst, you'll automate processes with SQL and Python, analyze data documentation, and collaborate with teams to enhance data management and analytics.

The Senior Data Engineer will implement quality data solutions, build pipelines, analyze raw data, develop tools, and collaborate with teams to meet business objectives.

Build and maintain scalable data pipelines in healthcare; develop solutions for data ingestion and modeling; collaborate with teams; ensure data quality and compliance, and explore AI tools.

Design and develop ML/DL algorithms and architectures for automated data analysis, build scalable ETL pipelines, and work collaboratively on projects.