Top Data & Analytics Jobs in San Francisco, CA

Define enterprise-scale data architecture across batch, streaming, warehouse, lakehouse, OLTP, OLAP, AI, and vector-store use cases. Establish standards for data quality, governance, lineage, access, observability, SLAs, and modeling. Serve as a technical escalation point, influence roadmaps, implement AI-enabled workflows, and mentor engineers through hands-on architecture, coding, reviews, and technical guidance.

Lead and grow a global data engineering team while building foundational cloud data platforms and scalable pipelines on GCP. Oversee data modeling, DataOps, reliability, governance, AI-ready data, CI/CD, monitoring, and stakeholder delivery. Establish engineering standards, SLAs, quality controls, architecture practices, and AI-assisted development workflows. Partner across business and technology teams to enable self-service analytics and data-driven decision-making.

Lead product analytics end-to-end: define metrics and measurement frameworks, analyze user behavior and product performance, build dashboards and self-service analytics, synthesize internal and market data, and deliver strategic recommendations to influence product roadmap and business outcomes while partnering cross-functionally.

Design and govern large-scale data architecture (warehouses, lakehouses, streaming), define standards for data quality, modeling, governance, and observability, embed AI/agent workflows, mentor engineers, and influence cross-functional roadmaps to enable scalable, production-grade data and analytics capabilities.