Top Data & Analytics Jobs in San Francisco, CA

Leads data-driven digital product and service improvements, manages transformation programs and project portfolios, develops digital talent, oversees quality and budgets, and directs team performance. The role shapes digital strategy, supports product management processes, drives cybersecurity incident remediation, and builds organizational capability through coaching, collaboration, and leadership.

Maintains, integrates, validates, analyzes, and visualizes geospatial and real property data for facility and infrastructure portfolios. Develops maps, dashboards, web applications, and spatial analyses; supports data quality, business process modernization, system implementation, integration, and migration. Collaborates with engineers, facility managers, planners, real estate specialists, and government stakeholders while documenting workflows and supporting federal data governance requirements.

Supports enterprise asset management data migration and systems integration initiatives involving IBM Maximo. Analyzes source and target data, executes migration strategies, develops integration objects and interface components, validates exchanged data, performs quality reviews, and coordinates project workstreams. The role requires expertise in Maximo Integration Framework services, data governance, data management standards, enterprise platform integration, and large-scale integration programs.

Own Pfizer GH&B’s AI-ready Snowflake data warehouse, ontologies, data governance, quality, lineage, access controls, and production reliability. Lead architecture and maintenance for dashboards, data applications, and prediction models; establish testing, release, documentation, and incident processes; monitor AI/ML data quality and drift; direct contingent engineering resources; and align business-specific data strategy with enterprise standards while influencing stakeholders without direct authority.

Lead an eight-person Analytics Engineering team and set the strategy for trusted, AI-ready self-service data. Own semantic models, governed metrics, data modeling, BI tools, LLM-powered data access, evaluation and telemetry systems, and production data applications. Establish governance, security, testing, deployment, and monitoring standards; define the long-term roadmap; partner cross-functionally; and hire, coach, and retain a high-performing team.

Leads an eight-person analytics engineering team responsible for trusted semantic models, governed metrics, curated datasets, enterprise BI, AI-powered data access, and production data applications. Establishes data and AI access strategy, builds evaluation and telemetry systems, sets engineering and governance standards, manages roadmaps and technical debt, and partners cross-functionally on adoption and business impact. Hires, coaches, and retains team members while guiding executive stakeholders and acting as customer zero for GitLab’s AI products.

Analyzes account portfolio whitespace, deal patterns, pipeline conversion, rep performance, budgets, forecasts, expenses, and revenue attribution. Builds models and executive-ready reporting to improve account planning, sales forecasting, demand generation, and spending decisions. Partners with Account Management, Finance, Contract Administration, and regional leaders to validate Salesforce data, reconcile variances, and deliver actionable recommendations.

Analyzes account portfolio whitespace, pipeline, deal patterns, campaign performance, rep effectiveness, forecasts, budgets, and expenses. Builds models and executive reporting to improve account planning, revenue conversion, forecast accuracy, and spending decisions. Validates Salesforce data, reconciles budgets and actuals, identifies risks and opportunities, and partners with Account Management, Finance, and other global stakeholders to deliver actionable recommendations.

The Senior Data Analyst gathers BI requirements, analyzes enterprise and offline datasets, writes and optimizes SQL queries, and develops dashboards using Power BI, Tableau, and Domo. The role translates business needs into technical specifications, creates dashboard wireframes, validates data, documents processes, and collaborates with engineering, product, and business teams. Expertise in the US trust business is required to ensure accurate, contextually appropriate analytics and BI solutions.

Partners with stakeholders to gather BI requirements, analyzes enterprise and offline datasets, writes complex SQL queries, and builds dashboards using Power BI, Tableau, and Domo. Translates business needs into technical specifications, wireframes, documentation, and data validation processes. Collaborates with data engineering, product, and business teams while applying US trust business knowledge to deliver accurate, contextually relevant insights.