Top Data Management Jobs in San Francisco Bay Area, CA

The Senior Manager, Performance Data Operations leads the Population Health Impact team, driving performance improvement initiatives, building complex datasets, and communicating insights to stakeholders. Responsibilities include data analytics, program management, and fostering cross-functional relationships.

Lead end-to-end data migration strategy and execution for complex franchise partners—perform discovery, map legacy data, troubleshoot imports, align stakeholders, and build scalable playbooks to standardize data delivery and ensure seamless platform transitions.

Manage video-language data projects, collaborate with external partners, ensure data quality, and work cross-functionally with teams to advance data operations.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights; manage people, mentor staff, partner with product and engineering, and build accessible data products and measurement practices.

Lead a data services team to design, automate, and oversee data processes. Oversee data extraction, transformation, modeling, validation, and quality reviews. Mentor and manage staff, monitor metrics, manage workloads, collaborate with stakeholders, ensure deliverable accuracy and confidentiality, and drive continuous improvement and strategic initiatives.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Lead acquisition, cleaning, validation, storage and protection of datasets to support reporting and analysis. Design and execute data architectures, policies and ETL pipelines (SSIS, ADF) using cloud platforms (Azure Synapse, Snowflake, Databricks). Deliver dimensional models, visualizations, and lifecycle governance to make complex data accessible and drive business insights.

The Clinical Data Manager will manage research databases, oversee EHR to EDC automation, ensure data quality, and perform statistical analyses.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

As a Senior Manager, R&D Data Steward, you will oversee stewardship of Pharma R&D data, ensuring data quality and compliance across the R&D value chain. You will lead a team, operationalize data governance, and drive improvements in data management processes, leveraging automation and cross-functional collaboration to enhance data-driven insights.

The Senior Manager, Data Steward (AI) will lead data stewardship initiatives in Pharma R&D, ensuring data quality and governance while mentoring a team and collaborating across departments to enhance data usability for insights and compliance.

The Manager R&D Data Steward oversees data governance, quality management, and stewardship of R&D data, ensuring compliance and integrity across data products and leading a team to support data management initiatives.

Lead a global, hands-on data engineering team building large-scale Databricks/PySpark pipelines, production datasets, customer-facing data feeds, AI-ready analytical datasets, and data quality/observability systems. Partner cross-functionally, use AI coding tools to accelerate delivery, and ensure operational excellence, reliability, and documentation for investor-facing products.

Own the conversion of raw alternative datasets into scalable, AI-ready data products. Define methodologies, metric definitions, and guardrails for AI-driven insights. Partner with engineering, product, and customers to expand use cases, ensure data quality, validate changes, and manage incidents to deliver reliable, explainable data products at scale.

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

The Enterprise Data Engineering & Platform Manager will lead data modernization initiatives, support AI/ML, manage data pipelines, and ensure platform reliability within a healthcare context.

Manage and grow a data engineering team, overseeing the design and maintenance of data platforms using Snowflake, dbt, and Azure. Drive best practices in data management and ensure reliable data movement and quality.

The Exposure Data Manager leads analytics to understand exposure patterns, enforces data standards, ensures data quality, and collaborates across departments for effective exposure management.

The Data Engineering Manager will lead a team, driving technical growth, fostering collaboration, and ensuring effective data architecture and systems.

Lead a team of data engineers in designing and maintaining scalable data infrastructure and pipelines, ensuring data integrity and decision-making support.

The Data Product Manager will execute timely data deliveries, collaborate with vendors and teams, and enhance the quality of data products to support healthcare stakeholders.

The Clinical Data Manager oversees the quality and integrity of clinical trial data, ensuring compliance with protocols and regulations while collaborating with various teams.

The Senior Clinical Data Manager oversees clinical trial databases, mentors junior staff, and ensures data quality and compliance with regulatory standards.

Lead strategic data evolution for Fund Administration clients, building dashboards, managing stakeholders, and translating business needs into actionable insights.

Develop and maintain operational and research datasets, translate requirements into SQL queries, build reports and data marts, enforce data access/security, document dataset construction and SOPs, and lead data quality and optimization initiatives across research support functions.