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

Build and operate production data pipelines, models, and data products supporting finance, accounting, treasury, compliance, and regulatory reporting. Partner cross-functionally to define requirements, model on-chain and internal data, and ensure data reliability through reconciliation, quality checks, monitoring, and alerting. Use SQL, Python, cloud data warehouse, Airflow, dbt, and AI tooling. Mentor engineers, review technical work, document systems, and communicate data concepts to technical and non-technical audiences.

Own supervisory data management and governance as a subject matter expert. Define data quality rules, metrics, monitoring, issue remediation, taxonomies, metadata, and cataloging practices. Partner with business, IT, and platform teams to improve data reliability, accessibility, lifecycle management, and future AI readiness. Translate business needs into technical requirements, facilitate adoption of governance practices, and communicate recommendations to technical and executive audiences.

Build reliable ETL infrastructure, scalable data pipelines, and trusted datasets serving product and business teams. Partner with data scientists and stakeholders to model data, monitor pipelines, define delivery SLAs, automate workflows, and enable self-service analytics and AI-assisted data exploration. The role requires strong SQL, cloud data-platform expertise, object-oriented programming, data modeling, and experience delivering production-scale data solutions.

Own business scorecards, dashboards, KPI reporting, and ad-hoc analyses focused on subscriptions, billing, revenue, retention, churn, engagement, and monetization. Translate ambiguous business questions into actionable recommendations, partner with Product, Finance, Marketing, Content, and Operations, and present executive-ready insights. Improve metric governance, data quality, and analytical practices across the organization.

Own people-data pipelines, organizational mapping, resource reporting, data transformations, reconciliations, and automated internal tools for Engineering, Product, and Design. Support headcount and resource planning, operating calendars, software capitalization, data governance, executive dashboards, and ad hoc workforce analysis. Partner with HRIS, Finance, Talent Acquisition, and EPD leadership to improve data integrity and operational decision-making.

Owns Sales and Servicing data as a trusted, governed, discoverable, and AI-ready enterprise asset. Defines data standards, quality controls, metadata, lineage, and business definitions while resolving complex data issues. Partners with AI, engineering, product, governance, and business leaders to enable sales effectiveness, client insights, servicing automation, intelligent routing, and self-service use cases. Leads cross-functional decision-making and translates complex data concepts into actionable business recommendations within a regulated financial services environment.

Build and maintain scalable GTM data pipelines, marts, semantic models, and dashboards supporting headcount planning, quota attainment, pipeline, and sales effectiveness. Partner with GTM analysts and stakeholders to establish reliable metrics, enable data tools, document systems, and develop AI-powered natural-language data querying capabilities. Translate complex data concepts for executives and engineers while ensuring high-quality, maintainable data products.

Designs and maintains scalable data pipelines and infrastructure, establishes data governance and quality standards, and drives technical decisions across Headway’s data platform. Partners with Product, Engineering, Analytics, Data Science, Infrastructure, Finance, and Insurance Systems to improve architecture, performance, reliability, security, and AI-readiness. Ensures data is complete, traceable, trustworthy, and suitable for powering internal tools and AI-driven insights.

Lead Airwallex’s global product-led growth measurement and operating systems. Own funnel and customer journey analytics across acquisition, onboarding, activation, transactions, retention, and expansion. Build KPI frameworks, dashboards, experimentation processes, tracking standards, QA systems, and performance reviews. Partner cross-functionally to improve CRM, marketing automation, customer data, attribution, and reporting. Translate ambiguous growth priorities into measurable outcomes and scalable execution.

Lead the architecture and development of Vercel’s financial data platform supporting revenue recognition, consumption-based billing, forecasting, reporting, and compliance. Build reliable batch and real-time pipelines using Kafka, ClickHouse, Tinybird, and Snowflake; ensure data governance, lineage, auditability, and accuracy; partner with Finance, Accounting, RevOps, Security, and Audit; drive architecture and roadmap decisions; and mentor engineers.