Top Data Management Jobs in San Francisco Bay Area, CA

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.

Manages HR data, analytics, reporting, dashboards, pipelines, integrations, and automation. Supports compensation, performance management, workforce planning, HRIS maintenance, and employee listening initiatives. Builds data models and AI integrations, audits data integrity, develops actionable insights, and presents findings to HR and executive leadership. Requires strong compensation expertise, advanced Excel, HRIS and BI experience, scripting, data modeling, and handling confidential information.

Lead and mentor a data engineering team building scalable customer-focused data solutions. Hands-on technical ownership, architecture guidance, and delivery of data ingestion, transformation, and reporting. Advance AI-enabled development practices, set technical standards, and foster a collaborative, accountable engineering culture to improve speed, quality, and reliability.

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.

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 R&D data stewardship across metadata, cataloging, data products, profiling, quality, governance, and compliance. Uses Informatica, SQL, Databricks, Python, and PySpark to curate data, automate workflows, define quality controls, and resolve complex issues. Applies AI-assisted stewardship and semantic data concepts while collaborating with technical and business stakeholders. Coaches other stewards, supports audit readiness, and improves stewardship standards and operating practices.

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.

Develop statistical, machine learning, and deep learning models to measure the impact of pharmaceutical HCP, DTC, and Medical Affairs campaigns. Partner with internal and external clients, provide analytical insights and methodological guidance, consult with sales and market research teams, and coach an offshore analytics team. The role requires applying causal inference, healthcare and pharmaceutical data expertise, and clear communication of findings to clients and executives.

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.

Leads and develops a team of Conversion Data Analysts, owning workload prioritization, delivery quality, and performance outcomes. Uses KPIs and data to identify risks, guide decisions, and improve high-volume conversion workflows. Partners with project management, Engineering, Product, Support, and leadership to ensure accurate data mapping and successful customer onboarding. Requires people leadership, SQL, Excel, data validation, CRM, and conversion tooling experience.

Manages the enterprise Data Governance and Analytics Center of Excellence, leading staff, governance initiatives, analytics strategy, maturity modeling, budgets, vendors, and planning. Coordinates data quality, stewardship, privacy, acquisition, and release programs while partnering with data scientists, engineers, technology governance teams, and business stakeholders. Develops executive presentations, aligns enterprise definitions and algorithms, establishes standards, and ensures analytics projects and business cases meet organizational objectives and deadlines.

Leads data strategy and analytics for the Risk/Credit team, translating complex datasets into insights for Credit, Operations, Marketing, Product, and Finance. Responsibilities include automating Python/R workflows, building Tableau dashboards, partnering with Data Engineering on Databricks workflows, conducting strategic analyses, monitoring data quality, presenting recommendations to leadership, and documenting analytical methodologies. The role requires strong SQL, cloud data warehouse, visualization, analytics programming, distributed computing, and version-control expertise.

Lead the Data & ML Platform team, overseeing data engineering, real-time systems, and ML enablement, while building reliable, scalable data platforms and improving data architecture.

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.

Lead and grow a Data Engineering team to build a scalable analytics platform. Set technical direction for dbt and Snowflake, raise analytics engineering standards, enable domain experts to contribute high-quality models, introduce AI-assisted workflows, and partner cross-functionally to ensure reliable, understandable enterprise data.

Leads and scales a global data engineering and analytics team while remaining hands-on with architecture, pipelines, data quality, dimensional modeling, dashboards, reporting, and customer-facing deliverables. Owns the analytical data platform supporting clinical, operational, product, financial, and customer data. Partners with cross-functional stakeholders, investigates complex data issues, improves platform reliability and security, and mentors engineers.

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.