Top Healthtech Data Engineering Jobs in San Francisco, CA

The Senior Data Architect will lead the design of scalable data solutions, ensuring alignment with business requirements and data governance principles while mentoring junior architects.

As a Machine Learning Infrastructure Engineer, you will build and maintain infrastructure for ML model training, optimize deployment, collaborate across teams, and improve internal tools for ML workflows.

The Analytics Engineer will build data models and pipelines for reporting and analytics, improving data infrastructure for ML and AI products, and setting processes for data collection and analysis.

As Data Engineering Lead, you'll own SuperDial's data platform, scaling the data warehouse and pipelines while leading analytics workflows to support product and operational insights.

Design and build NexHealth's financial data foundation, including pipelines, models, and dashboards for revenue reporting and forecasting.

As a Staff Data Engineer, you'll architect secure data systems, build pipelines, enforce best practices for sensitive data management, and mentor teams across Tonal.

Design and develop innovative deep learning methods for biomolecular design, collaborating with biology teams, prototyping new algorithms, and presenting results.

Lead design, development, validation, and deployment of scalable NGS bioinformatics workflows for regulated diagnostics. Drive assay study design, ML/statistical evaluation, regulatory compliance, documentation, and mentor junior team members.

Design, build, and optimize ETL pipelines and data workflows. Collaborate with teams to translate requirements into data solutions, ensuring data quality and efficiency.

As a Senior Analytics Engineer, you will own Solv's analytics stack, focusing on data pipeline efficiency, customer-facing analytics, and AI-powered tools, working with internal teams to improve metrics, dashboards, and data visibility.