Top Senior 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.

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.

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

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

The Data Scientist in Finance will analyze financial data, create dashboards, collaborate on data engineering, and find improvements for the business.

Leads the enterprise data platform strategy, architecture, governance, and evolution. Manages a central data team and enables federated self-service analytics across business functions. Builds AI-ready data pipelines, RAG and Graph RAG architectures, custom data applications, observability, cost optimization, and AIOps capabilities. Requires hands-on expertise with Snowflake, dbt, modern ETL, Python, SQL, CI/CD, and Data Mesh architectures, along with 5+ years leading technical data teams.

Build and maintain Engine X performance dashboards, reporting frameworks, data models, and complex SQL analyses using Snowflake. Track card, booking, rewards, spending, and retention metrics; investigate anomalies; support A/B tests; document metric definitions; and communicate findings to product, finance, and leadership. Collaborate with analytics and data engineering teams to validate pipelines and improve data quality.

Leads analytics for Pricing and Supply, managing a team of approximately eight analysts. Partners with cross-functional leaders to prioritize analytical work, build dashboards and decision frameworks, improve metric quality, and generate insights into pricing, supplier coverage, marketplace performance, conversion, margin, and customer behavior. Coaches analysts, establishes scalable analytics processes, and collaborates with data engineering teams to improve data models, tooling, and self-service capabilities.

Own product analytics and customer success data domains by building governed models for product usage, feature adoption, customer health, onboarding, renewals, churn, expansion, and net revenue retention. Partner with Product, Customer Success, RevOps, Finance, and analysts to create semantic models, metric definitions, instrumentation, documentation, alerting, and self-service tools. Use dbt, Snowflake, Omni, Hex, and AI-assisted development to turn ambiguous stakeholder questions into durable data products.