Top Senior Data Engineer Jobs in San Francisco Bay Area, CA

Transform Electronic Health Records (EHR) data into structured assets, build scalable data pipelines, and apply Generative AI techniques for analytics within a healthcare-focused team.

As a Staff Data Engineer, you'll architect and model data, create ETL pipelines, and standardize datasets for compliance teams. You'll guide best practices and lead data solutions while collaborating with various stakeholders.

As a Senior Data Engineer, you will design and maintain data pipelines, define governance standards, and collaborate across teams to enhance Headway’s data architecture.

Lead data engineering projects within the Sales Analytics team at Visa, developing complex data solutions for business intelligence, creating scalable data pipelines, and ensuring high data quality. Engage with various teams to support initiatives and empower business insights.

The Data Engineer will design, build and maintain scalable ETL pipelines and data integrations, ensuring data governance and operational excellence while collaborating with cross-functional teams.

The Staff Data Engineer will design and optimize data pipelines, collaborate with stakeholders, mentor team members, and lead architectural decisions in data infrastructure.

As a Senior Data Engineer, you'll design and develop models to integrate diverse data sources for analytics and AI applications, ensuring data consistency and quality across domains.

Design and build secure data pipelines, lead data architecture, collaborate across teams, ensure data quality, and mentor other engineers.

The Senior AI Data Engineer will design and maintain datasets for AI models in cybersecurity, ensuring data quality and relevance while collaborating with teams.

The Principal Data Engineer will own data infrastructure, design data pipelines, drive improvements to data systems, and collaborate across teams for optimal data delivery and performance.

Seeking an experienced Data Engineer to design and optimize data infrastructure, build scalable pipelines, and ensure data quality and governance.

The Senior Data Engineer will maintain ChowNow's data platform, enhance data pipelines, work with data scientists, and improve data quality and accessibility, contributing to executive decision-making and business growth.

Develop and productionize a next-gen Dispatch System, build predictive models, automate processes, and lead a small team in optimizing operations.

The Data Engineer will build scalable privacy-centric data frameworks, engineer data pipelines, and ensure compliance with privacy regulations at Netflix.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

Lead the evolution of SimplePractice's data stack, building scalable systems for analytics, reporting, and product insights in a fast-paced environment.

The Senior Data Engineer will develop and maintain data pipelines, collaborate with Analysts, and ensure high code and data quality on the Hungryroot Analytics model.

Lead design and delivery of data solutions in Adobe Experience Platform, optimize data models, mentor junior engineers, and drive strategy.

As a Data Engineer, you will design data storage systems, build ETL pipelines, optimize data reliability, and collaborate across teams, leveraging modern technologies for data management and processing.

As a Data Engineer, build efficient data processing systems, model data to support analytics, and collaborate with teams to enhance Netflix's data-driven culture.

The Staff Data Engineer will design and implement data warehousing solutions, lead design discussions, mentor engineers, and tackle complex data challenges while ensuring data quality and insights delivery.

The Lead Data Engineer will develop data infrastructure, manage event structures, design storage architecture, and mentor engineers for better data practices.

The Senior Data Engineer will manage data pipelines, ensuring data quality and optimizing ML workflows while supporting multiple engineering teams across locations.

Design and maintain scalable data pipelines, collaborate with cross-functional teams, manage data architectures, optimize Snowflake performance, and enhance data workflows.

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