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

The Lead Data Engineer will design and expand Nuna's Data Platform, establish best practices, mentor team members, and collaborate with data scientists to optimize workflows. This role entails hands-on development, managing complex data sources, and ensuring data governance while contributing to innovative projects in healthcare.

The Lead Data Engineer will develop and optimize data infrastructure, build scalable ETL pipelines, manage data warehouses and lakehouses, ensure data quality, and collaborate with data science teams to support ML model deployment.

Looking for a Data Engineer with 5+ years of experience in a SaaS environment. Must be proficient in SQL, dbt, Python, and have experience with data engineering tools and cloud services. Responsibilities include owning data workflows, ensuring data quality, and leading data modeling efforts.

The Staff Machine Learning Engineer will lead a team focused on Generative AI systems, enhancing AI infrastructure and product vision. Responsibilities include driving technical direction, mentoring engineers, developing algorithms for user connectivity, and collaborating with product managers to integrate Machine Learning into user experiences.

The Senior Analytics Engineer at Druva will develop data models, reports, and dashboards to promote data-driven decision-making. Responsibilities include managing data requests, maintaining analytics databases, and using SQL and Python for data solutions, all while collaborating across teams for strategic initiatives.

As a Manager of Privacy & Data Protection, you will lead Strava's global compliance with data protection laws, oversee internal privacy processes, and support cross-functional privacy initiatives. Responsibilities include maintaining risk registers, reviewing data agreements, and implementing technology solutions for privacy operations while collaborating closely with stakeholders across the company.

The Lead Data Engineer will architect, build, and maintain data pipelines to support AI products and analytics at Lumos. Responsibilities include optimizing data pipeline performance, ensuring reliability and scalability, and integrating various data streams to derive business insights. The role requires collaboration with multiple stakeholders and a focus on automation and best engineering practices.