Top Hybrid Data Engineering Jobs in San Francisco, CA

Lead and deliver data-driven commercial analytics projects for life sciences clients, design/implement data platform and ETL solutions, analyze data and present insights, manage client relationships and project teams, mentor junior staff, and contribute to business development and internal data warehouse initiatives.

Lead design and implementation of the data foundation for Visa Marketing 360: integrate and cleanse internal/external sources, build data pipelines and scalable data models, ensure data quality and governance, develop analytics dashboards and AI-driven automation, support campaign measurement and personalization, and collaborate with product and marketing teams to enable data-driven marketing execution.

Design and maintain scalable data pipelines, ensuring accurate delivery and governance of data across the organization while collaborating with cross-functional teams.

Execute and validate data migrations into Salesforce from multiple sources, transform and reconcile datasets, troubleshoot integrity issues, document migration steps for auditability, and support post-migration data hygiene in collaboration with Operations, Analytics, and Engineering.

The role involves automating data analytics processes, preparing datasets, and collaborating with stakeholders to enhance People reporting frameworks.

The Senior Analytics Engineer will create and maintain data models for cancer screening insights, collaborating across teams to ensure accurate analysis and decision-making, while exploring AI and automation tools to improve workflows.