Top Hybrid Data Engineering Jobs in San Francisco, CA

As a Data Analytics Engineer, you'll build and manage data models in Snowflake, structure datasets for optimal AI performance, and own data transformation while ensuring quality and accessibility for all teams.

Lead transformation of Mastercard's enterprise data ecosystem. Define architecture of cloud-native data platforms, establish governance, and implement data engineering best practices.

As a Senior Associate in Data Engineering at PwC, you will design and implement data architecture strategies, analyze complex issues, mentor junior members, and build client relationships while ensuring adherence to project standards.

The Senior Data Engineer will develop and maintain a high-quality data platform, implementing features, performing code reviews, and collaborating with teams to meet requirements.

Lead design, build, and maintenance of scalable data pipelines and lakehouse infrastructure using PySpark, Databricks, and Airflow. Own data & ML platform (Terraform, Databricks), improve observability, data quality, and developer tooling, and partner closely with Data Science and engineering teams.

The Founding Data Engineer will manage the company's data models, ensure metric integrity, and work with various teams to deliver reliable metrics and reporting systems.

Design and implement near real-time data pipelines and reporting systems. Ensure reliability and scalability of distributed data systems and collaborate with cross-functional teams.

The Analytics Engineer II will build data models, ensure data quality, and support business teams with analytics needs.

As a Senior Analytics Engineer at Kikoff, you will build data pipelines, automate financial reporting, ensure data accuracy, and collaborate across teams to deliver insights driving financial performance.

Design and build Retool's data infrastructure, optimize ETLs, ensure data access and quality, and collaborate with stakeholders across the company.