Top Senior Data Management Jobs in San Francisco Bay Area, CA

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

Lead development and execution of data-driven strategies, manage project planning and delivery, mentor and coach team members, ensure quality and ethical standards, design cloud data architectures and governance frameworks, analyze complex datasets to produce actionable insights, and drive continuous improvement using advanced analytics and modern data technologies.

Leads client-focused data analytics initiatives within PwC’s Risk & Regulatory practice. Develops business intelligence, visualization, and advanced analytics solutions using Python, Oracle Business Intelligence, QlikView, and Spotfire. Builds stakeholder relationships, validates outcomes, drives process improvement, and applies systems thinking to solve complex business challenges. Oversees scalable deployments and coaches teams through ambiguous situations while delivering strategic insights and improved client performance.

Lead development and implementation of data governance strategies, manage client accounts and deliverables, supervise and mentor teams, analyze data to inform business decisions, ensure compliance with firm standards, and identify improvements in data management processes.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Leads the enterprise data platform strategy, architecture, governance, and evolution. Manages a central data team and enables federated self-service analytics across business functions. Builds AI-ready data pipelines, RAG and Graph RAG architectures, custom data applications, observability, cost optimization, and AIOps capabilities. Requires hands-on expertise with Snowflake, dbt, modern ETL, Python, SQL, CI/CD, and Data Mesh architectures, along with 5+ years leading technical data teams.

Leads a data engineering team responsible for data modeling, batch and streaming ETL pipelines, analytics-ready datasets, data governance, and data quality. Hires, coaches, and manages engineers while setting technical direction and partnering with engineering, product, and business stakeholders. Oversees scalable data foundations across regulatory, customer, business, content, and growth domains, and advances practical AI automation and AI-ready infrastructure.

Leads and develops a Data Platform engineering team while owning delivery of complex data initiatives. The role establishes delivery discipline, assesses technical and implementation risks, partners cross-functionally, and drives production reliability, data quality, observability, incident management, and on-call readiness. It also guides the evolution of scalable data ingestion, transformation, lakehouse, cloud architecture, governance, and reusable platform capabilities.

Leads data engineering and AI platform delivery for enterprise operations. Designs scalable AWS and Databricks architectures, builds ELT pipelines with Airflow, develops data models, and establishes governance, security, quality, monitoring, and compliance controls. Partners with stakeholders to translate business needs into production solutions, guides platform evolution, and supports AI-powered automation, agentic architectures, and enterprise integrations. Provides technical leadership and subject-matter expertise across data, analytics, and AI initiatives.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

Lead a remote analytics team to deliver dashboards, data products, and decision-support tools. Oversee project plans, stakeholder engagement, data platform modernization, ETL/automation, Tableau/Power BI deployments, statistical modeling, QA, metadata, and staff mentoring to support federal social service programs.

Leads data engineering and data science teams, setting strategy and delivering scalable pipelines, data architecture, models, analytics infrastructure, and data governance. Partners with product, analytics, and business stakeholders to prioritize initiatives, assess upstream changes, maintain data quality, and support Snowflake-based warehousing. This hands-on leadership role includes mentoring staff, contributing to technical codebases, and advancing data science and engineering solutions.

Leads a team of business and data analysts while owning the analytics roadmap for commercial, sales, and go-to-market functions. Translates business needs into analytical frameworks, KPIs, dashboards, models, and reporting strategies. Partners with senior stakeholders and cross-functional teams to drive data-informed decisions, governance, quality, and best practices. Provides mentorship, oversees solutions using modern data tools, and presents recommendations supporting planning, forecasting, and execution.

Owns governance, quality, standards, and lifecycle management for eight master data domains across ERP and related systems. Administers NetSuite master data, defines validation and error-proofing controls, resolves data discrepancies, maintains audit-ready documentation, and reports quality KPIs. Partners with IT, Supply Chain, Finance, Commercial, Regulatory, Customer Care, and other teams on integrations, migrations, product launches, compliance, serialization, and pricing. Provides cross-functional guidance and drives data discipline without direct authority.

Manages client, compliance, and performance reporting across healthcare programs using eligibility and claims data. Leads reporting analysts while remaining hands-on with advanced SQL, dashboards, data crosswalks, validation, reconciliation, root-cause analysis, and data-quality monitoring. Partners with data engineering and clients to resolve upstream issues, establish reporting standards, and guide the analytics roadmap.

Manages a data engineering team responsible for scalable, reliable data pipelines, infrastructure, and analytics tooling. Provides mentorship, performance management, and technical leadership while coordinating with product, analytics, finance, compliance, engineering, and regulators. Prioritizes cross-functional projects, supports data architecture and governance, ensures performance and reliability, and operates within strict regulatory and audit requirements.

Analyzes, cleanses, validates, and prepares operational datasets for mailing, email, reporting, billing, and processing activities. Develops Databricks queries and Alteryx workflows to automate processes and improve data quality. Performs audits, reconciliations, root-cause analysis, and corrective actions while maintaining governance and security compliance. Provides actionable insights, mentors junior analysts, communicates findings, and leads continuous improvement initiatives.

Lead design and rollout of a fit-for-purpose data governance program: manage data lifecycle, implement governance frameworks and tools, drive data catalogs/lineage, upskill stewards, define KPIs, and partner cross-functionally to improve data quality, compliance, and usability.

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.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Manage and improve corporate giving data systems: build and maintain Tableau/Excel dashboards, respond to ad hoc data requests, clean and govern community data, administer Bonterra/CyberGrants, and lead project management for giving programs and strategic initiatives while partnering with enterprise stakeholders.

Leads enterprise business intelligence and analytics strategy, owning the vision, roadmap, KPIs, and adoption measures for insight products. Manages data engineering and analytics teams, partners with senior leaders, translates business questions into analytical solutions, and delivers executive-ready insights. Provides technical oversight for data models, pipelines, semantic layers, data quality, scalability, and metric standardization across transformation, sales, operations, sustainability, and other enterprise domains.

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.