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Data Modeling Jobs in San Francisco
14 open positions · Updated 1 week ago
14 Data Modeling roles across 11 companies, most in Backend; typical advertised salary $194k
Who is hiring (11 companies)
Work arrangement: 3 hybrid · 2 on-site · 9 not stated
Advertised salaries: p25 $176.7k · median $194k · p75 $218k (from 10 disclosed annual salaries, USD)
Counts are open roles Joblaze currently tracks on company career pages for this exact skill/location; salaries are advertised minimums, annual, converted to USD.
Showing 14 of 14 positions
Search with filters →Lead the platform strategy for Midstream's AI-native products, transforming complex healthcare data into actionable intelligence.
Join Okta as a Staff Software Engineer to build secure, scalable enterprise software that impacts thousands of users daily.
Join Okta as a Staff Software Engineer to build secure, scalable enterprise software that impacts thousands of users daily.
Join Okta as a Staff Engineer to build enterprise-grade software for access governance at scale.
Join Okta as a Principal Software Engineer to shape enterprise-grade software for access governance at scale.
Join Peregrine as a founding product marketer to drive commercial success in the private sector with an AI-enabled data platform.
Join Benchling as a Product Manager to shape the future of biotech R&D with AI-driven data modeling.
Own the backend architecture of a clinician-facing platform at Frontera Health, impacting pediatric healthcare with cutting-edge technology.
Join Handshake as a Software Engineer to shape AI applications for enterprise customers in a fast-growing company.
Join EliseAI as a Junior Research Scientist to develop machine learning models in a fast-paced startup environment.
Join Discord as a Staff Data Engineer to lead the technical vision for our analytical data infrastructure supporting millions of users.
Lead the strategy and implementation of Databricks' SAP platform to transform finance operations with AI-powered workflows.
Lead the Research Data Platform team at Anthropic to enhance data systems for AI research, ensuring usability and trustworthiness.
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