Top Data & Analytics Jobs in San Francisco Bay Area, CA

Own and build canonical data models and metric definitions using dbt and cloud warehouses. Create tests, documentation, lineage, and data quality checks; reconcile metrics across teams and payer customers; partner with analysts, data scientists, product, engineering, and finance; optimize warehouse performance, cost, and PHI-aware access patterns.

Lead architecture and standards for CoreWeave's enterprise data ecosystem: design lakehouse/streamhouse architectures, modeling and semantic layers, governance, data quality, lineage, observability, and reusable data products. Drive cross-domain solutions, resolve performance and scalability constraints, evaluate core data technologies, conduct architecture reviews, and mentor senior engineers.

The role involves managing and improving data quality pipelines for GTM systems, optimizing AI workflows, and overseeing offshore teams to ensure accurate data detection and resolution.

Design and implement scalable data pipelines and a SOC2-compliant data warehouse. Support analytics and ML teams, enable real-time and batch ETL, mentor data engineers, and collaborate cross-functionally to drive data-driven decisions.

Lead analytics strategy and decision support across Product, Growth, Revenue, Operations, and Finance. Perform deep-dive analyses, design experiments, build predictive models and ML/AI prototypes, create trusted reporting and dashboards, ensure data quality, automate workflows, and partner with stakeholders to drive measurable business outcomes. Act as a primary analytics partner, prioritize work, communicate recommendations, and mentor analysts informally.

Lead analysis and insights for sports game titles; translate product and business needs into actionable, data-driven recommendations; build reports and visualizations; develop scalable self-service tools; mentor analysts and partner with Product, Marketing, and Commercial teams to drive player and business outcomes.

Design and implement scalable data models and ETL pipelines (batch and streaming), ensure data quality/SSOT, collaborate with product and platform teams to resolve issues, contribute to data governance, and explore practical integrations between data engineering and AI.

The Director of Biostatistics leads a team in clinical research, developing statistical plans, collaborating across departments, and ensuring regulatory compliance.

The Senior Analyst in AML KYC will conduct detailed customer onboarding, monitor client relationships for compliance, and update KYC records while utilizing AI tools for efficiency.

As a Senior Data Engineer, you will automate processes, optimize data handling, build data products, and govern data while mentoring junior engineers.