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

Build and maintain scalable dbt data models, transforming raw data into trusted, documented datasets. Own warehouse data modeling and metric definitions, establish testing and code review standards, monitor data quality, optimize query performance, and troubleshoot reporting discrepancies. Partner with engineers, analysts, and business stakeholders to translate business needs into reliable pipelines. Mentor junior engineers and contribute to technical best practices and tooling decisions.

Own measurement strategy and performance improvement for Snap’s advertising measurement solutions. Lead experimental design, causal analytics, benchmarking, meta-analyses, governance, and scalable measurement initiatives. Advise executives and external partners, influence product roadmaps, develop thought leadership, and build analytical fluency across teams. Apply advanced statistics, SQL, AI tools, dashboarding, and data visualization to guide advertising efficacy decisions and identify innovation opportunities.

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.

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.

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.

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.

Build and operate reliable data systems and products supporting clinical operations, drug evaluation, business development, analytics, machine learning, and AI agents. Responsibilities include designing pipelines, canonical data models, data contracts, warehouse transformations, quality and observability practices, governance for regulated data, and incident response. The role partners closely with Product Engineering and Data Science, uses AI-assisted development, contributes to architecture, and mentors other engineers.

Leads data analysis and advanced analytics workstreams for clients, using statistical modeling, machine learning, data visualization, and Adobe Experience Cloud technologies to improve operations and strategic decision-making. Manages project planning, budgeting, execution, and completion while mentoring teams, maintaining data integrity and security, building Tableau and Power BI dashboards, identifying business opportunities, and integrating innovative analytics practices.

Analyze complex data and develop managed data solutions, business intelligence tools, dashboards, metrics, and self-service capabilities. Partner with business and technology teams to deliver strategic insights, manage data quality, metadata, lineage, security, and access governance. The role requires scripting, querying, visualization, Snowflake development, and familiarity with cloud services and data governance.

The Economist will analyze travel and spending data to identify trends, craft insights, and present findings, serving as an economic advisor to leadership.