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

Designs and leads scalable batch and real-time data pipelines supporting AI/ML applications, LLMs, RAG workflows, predictive models, and executive data products. Responsibilities include data architecture, feature stores, governance, security, lineage, performance and cost optimization, and cross-functional technical leadership. The role partners with data scientists, program managers, executives, and engineering teams to deliver reliable enterprise data solutions.

Own the Marketing organization’s data and analytics strategy, including data structures, reporting requirements, governance, dashboards, and marketing funnel measurement. Partner with engineers, MarTech teams, vendors, and leadership to improve infrastructure, data quality, and operational efficiency. Lead executive-level performance analyses, operating-plan metrics, and C-suite reporting by translating complex cross-functional data into actionable strategic narratives.

Build and own scalable finance and revenue data pipelines, models, and datasets supporting ARR, NRR, bookings, billing, and revenue attribution. Ensure data quality, reliability, monitoring, reconciliation, and self-service access while partnering with Finance, Revenue Operations, Analytics, Product, and Engineering.

Serve as the strategic analytics partner to GTM leadership, connecting Finance, Revenue Operations, Product, Growth, and sales leaders. Build trusted analytics infrastructure, define metrics and reporting, develop scenario models, and translate complex business decisions into executive recommendations. Own recurring business reviews and the end-to-end view of sales performance across routes to market, helping leaders evaluate product, pricing, compensation, organizational, and market changes.

Own data integrity and reconciliation across Salesforce, Entity Master, and related platforms. Investigate discrepancies, duplicates, missing records, and synchronization failures affecting onboarding and client servicing. Perform root-cause analysis, develop reporting, document processes, and support automated data-quality initiatives. Partner with business, data operations, engineering, and IT teams to resolve systemic issues and improve workflows.

Build and scale data products supporting analytics, engineering services, and AI/ML models. Responsibilities include optimizing queries and data pipelines, developing data models and governance processes, administering ETL/ELT and reverse ETL orchestration, and creating documentation and training. The role also involves mentoring, interviewing, and hiring data engineers while helping define the organization’s data engineering strategy.

Lead end-to-end quantitative market research, including research planning, surveys, advanced statistical analysis, synthesis, and stakeholder presentations. Build and manage brand and sentiment measurement programs, identify customer and market trends, and provide strategic recommendations for growth and product opportunities. Partner with business leaders, promote research-driven decision-making, and mentor junior researchers while scaling the organization’s research practice.

Leads Apollo’s core data engineering organization, including Native Data, waterfall enrichment, and scraping platforms. Owns strategy, architecture, team growth, data acquisition, enrichment, synchronization, quality, freshness, monitoring, and large-scale ETL systems. Partners with executives and cross-functional teams to improve data coverage and reliability, establish feedback loops, select vendors, and apply AI to data acquisition and maintenance.

Lead Notion’s Data Foundations team by setting multi-quarter platform strategy, developing engineers and technical leaders, and guiding complex initiatives across data lakes, streaming, distributed compute, governance, and reliability. Drive enterprise-ready capabilities including data residency, access controls, lifecycle management, and key management. Improve Kafka, Debezium, S3/Iceberg, Spark, EMR, and Athena scalability, reliability, usability, and cost efficiency while partnering across engineering, AI, search, infrastructure, and security teams.

Owns analytics and optimization strategy for advertising revenue across Zynga’s mobile game portfolio. Responsibilities include monitoring performance, diagnosing trends, designing A/B tests, identifying monetization opportunities, partnering with product, analytics, and data science teams, supporting AI and ML models, leading cross-functional initiatives, and mentoring analysts.