Top Data Management Jobs in San Francisco Bay Area, CA

Leads data analysis, reporting, performance evaluation, and dashboard development for federal transition assistance programs. Manages data integration, modeling, quantitative and qualitative analysis, program evaluations, executive reporting, and performance measurement. Translates complex data into actionable recommendations supporting operational effectiveness, strategic planning, modernization, and continuous improvement. Collaborates with government leaders, program managers, technical teams, and stakeholders. The role is remote with occasional travel for in-person meetings.

Leads enterprise analytics strategy, data integration, governance, reporting, dashboards, forecasting, and advanced business analysis. Manages analysts and partners with Sales, Pricing, Finance, Product Management, Operations, and executive leadership to translate complex data into actionable recommendations. Oversees Power BI dashboards, KPI frameworks, data quality, predictive modeling, and reporting automation to improve growth, profitability, pricing, and operational performance.

Leads the architecture, implementation, and evolution of enterprise data platforms, including Master Data Management, data lakes, lakehouses, and cloud data services. Manages data engineers and developers, establishes engineering standards, oversees Azure-based integrations and pipelines, and owns data applications, databases, security, governance, and production support. The role also directs technical strategy, manages multiple initiatives, and communicates architecture and delivery plans to stakeholders.

Leads and develops product, marketing, and data analysts while overseeing analytics strategy, prioritization, technical standards, experimentation, reporting, and data quality. Partners with Product, Marketing, Finance, Engineering, and recruiting to deliver trusted insights, scalable self-service analytics, and team growth. Requires strong SQL and Python skills, modern data-tool experience, analytics leadership, stakeholder communication, and at least five years in data roles with two years managing teams.

Lead and grow a data engineering team, define data platform architecture and reliability (warehouse, ingestion, transformations, orchestration), set engineering standards, partner cross-functionally to support analytics and ML, and translate technical decisions for executive stakeholders.

Leads the enterprise analytics organization, managing Analytics Engineers, Data Analysts, and BI Developers. Defines analytics strategy, delivers executive dashboards and operational reporting, establishes KPI and governance standards, builds semantic models and curated datasets, and drives self-service BI adoption. Partners with Engineering, Product, Finance, Operations, Customer Success, and executives to translate business needs into trusted analytical solutions while developing talent and prioritizing analytics initiatives.

Leads the enterprise analytics organization, managing Analytics Engineers, Data Analysts, and BI Developers. Defines analytics strategy; delivers executive dashboards, KPI scorecards, operational reporting, semantic models, and self-service BI. Establishes data governance and metric standards, ensures data quality, partners with Engineering, Product, Finance, Operations, and executives, and translates business questions into actionable analytical solutions. Mentors analytics talent and drives prioritization, adoption, and measurable business outcomes.

Leads product, formulation, packaging, and SKU onboarding across master data and PLM systems. Defines data standards, hierarchies, workflows, playbooks, SLAs, and quality metrics; manages PLM operations, integrations, and system enhancements. Partners with R&D, Supply Chain, Regulatory, Commercial, Quality, and IT to govern product lifecycle data. Manages and develops a small analyst team while building scalable processes and resolving data issues.

Lead a team of data scientists to optimize Databricks infrastructure using data science for capacity planning, reliability, and performance improvements.

Own end-to-end analytics delivery for a client POD, translating business priorities into workplans, coordinating cross-functional teams, governing delivery and revenue KPIs, and managing risks through resolution. Perform hands-on data profiling, validation, reconciliation, exploratory analysis, automation, and quality reviews using SQL, Python, Databricks, and Excel. Create executive-ready KPI, revenue, and business-impact narratives, prioritize initiatives, support business cases, and identify opportunities for analytics automation and AI-enabled improvements.

Manage secure, compliant data environments, including governance policies, data architecture, integration, quality, security controls, audits, and performance optimization. Lead data analysis, reporting, documentation, and cross-functional collaboration while mentoring junior staff. The role requires protecting sensitive or classified data, maintaining access controls and encryption, and ensuring compliance with government and organizational standards.

Manage and mentor a data engineering team while leading Snowflake-based platform architecture, enterprise data integrations, governance, observability, and pipeline reliability. Partner with analysts, business leaders, product management, and engineering teams to improve trusted self-service data access. Establish engineering standards, modernize the data stack, optimize costs, and deliver an AI-ready data foundation supporting analytics, reporting, and future AI initiatives.

Build and own HRBP analytics: deliver dashboards, predictive models, ROI and program evaluation, AI-enabled workflows, data storytelling for executives, and scalable reporting systems while partnering with HRBP Operations and stakeholders.

As a Data Scientist, you will drive data-informed decisions at Anthropic by analyzing product usage, conducting causal inference, and collaborating across teams to enhance developer platform performance.

Manage CVS Health's data partnerships and monetization strategy, source new partnerships, ensure operational success, and drive data product adoption across analytics teams.

Manage operations for client engagements in the life sciences sector, leading projects, enhancing data processes, and developing data-driven solutions while maintaining client relationships.

Lead architecture and operations for the end-to-end data lifecycle: pipeline orchestration, dbt projects, cloud warehouse performance, dimensional modeling, data observability, HIPAA controls, and platform governance. Mentor a distributed data engineering team, partner with Analytics and Finance, and prioritize durable platform capabilities that enable BI, experimentation, and AI use cases.

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.