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Top Hybrid Data Engineer Jobs in San Francisco, CA
In this role, you will lead projects within the Data & Analytics team, focusing on advanced analytics to support finance and strategy. Responsibilities include managing data from various sources, creating models, generating results, and ensuring data integrity while communicating effectively with stakeholders to inform strategic decisions.
The Senior Database Administrator is responsible for managing SQL Server databases across various environments, ensuring performance, stability, and security. Key tasks include troubleshooting issues, optimizing queries, implementing backup plans, and collaborating with teams to improve processes and features.
As a Senior Machine Learning Quality Engineer at ServiceNow, you will design and review test automation frameworks for machine learning models, work with ML engineers to address functional requirements, establish metrics for test effectiveness, and create comprehensive test plans. Collaboration with both technical and non-technical team members is essential to ensure quality in AI and ML applications.
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The Senior or Lead Big Data DevOps Engineer will manage and optimize Big Data infrastructure across cloud environments. Responsibilities include enhancing efficiency, driving cross-team initiatives, managing architecture efforts, ensuring system reliability, and supporting operational tools and practices.
The Principal Machine Learning Engineer will lead the development and optimization of recommendation systems for Disney's streaming platforms. This role requires collaboration with various teams to innovate on personalized content experiences, manage stakeholder expectations, and drive company objectives related to algorithms and recommendations.
In this role, you will develop an AI/ML strategy to enhance customer support at Canva, lead the creation of natural language systems, collaborate with engineering teams, and leverage machine learning capabilities across the organization.
As a Senior Data Engineer at Gantri, you'll design and implement data pipelines and data warehousing solutions, ensuring data quality and performance. You'll collaborate with software engineers and cross-functional teams, create data models, and develop data visualization tools to support analytics and reporting, all while establishing data engineering best practices.
The Lead Data Engineer will develop and optimize data infrastructure, building ETL pipelines, managing data warehouses, and ensuring data system reliability. This role requires collaboration with Data Science and Analytics teams to integrate ML models and ensure data quality compliance with regulations.
Top hybrid Companies in San Francisco, CA Hiring Data + Analytics Roles
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