Top Senior Data Management Jobs in NYC, NY

The Associate Manager- Data Architect will lead data projects, develop data models and integration processes, ensure data quality, and mentor junior staff, while collaborating with clients to meet their needs.

The Associate Manager will lead the implementation of Master Data Management systems, manage client projects, coordinate with data vendors, and provide mentorship and insights to optimize commercial operations for life sciences companies.

The Manager of MDM leads projects for Master Data Management systems, working with teams to ensure successful client engagements in the pharmaceutical and life sciences sector.

Lead the Finance Reporting and Analytics team to drive growth through data-driven decision making, managing analysts and delivering insights via dashboards and predictive models.

Manage integration processes, analyze data quality, design reporting solutions, and facilitate integration teams while supporting enterprise initiatives.

Manage and optimize GTM tech stack, oversee Salesforce CRM, ensure data quality across systems, build data models, and create actionable insights for go-to-market strategy.

The Data Operations Manager leads a team ensuring data quality, manages incidents, drives process improvements, and communicates with stakeholders. They require strong SQL and team management skills.

Lead a team of Data Scientists, Analytics Engineers, and Data Engineers to drive messaging strategies through analytics and data science, ensuring collaboration across various business domains.

The Senior Data Manager will design, configure, and launch clinical trials on Citrus while managing data quality and collaborating with product teams and stakeholders.

Lead data strategy for Blue Owl Private Wealth by managing data integrity and analytics tools, improving operational frameworks, and ensuring effective project execution.

The Manager of Solution Consulting leads pre-sales engagements for Veeva Data Cloud, focusing on data consulting and client relationship management, while contributing to product strategy and project management.

The Senior Data Manager is responsible for acquiring, cleaning, and managing datasets, developing data architectures, and ensuring data accessibility for business analysis and reporting.

The Assistant Manager will lead data governance and analytics, manage the Data Warehouse systems, ensure data security, and develop policies for data management and compliance.

Lead and mentor a Data Engineering team, manage data operations, ensure compliance with HIPAA, and design scalable ETL pipelines while collaborating across departments.

Lead and manage a Data Science team focused on analytics, experimentation, and machine learning, driving insights for product and marketing strategies.

The role manages GCIB's data domain, ensuring regulatory compliance and operational excellence through stakeholder collaboration and strategic execution.

The Business Intelligence & Analytics Manager will enhance BI capabilities, create analytics pipelines, mentor teams, and collaborate to optimize data-driven decision-making across R2Net.

Lead AML transaction monitoring compliance, oversee data governance, and participate in business strategy. Apply analytics and build dashboards to translate risks into metrics.

Manage a team of analysts while analyzing data, reporting, and enabling AI/ML model deployment. Provide insights and automate processes.

Manage a team of data scientists to develop fraud detection models, mentor staff, and collaborate with leadership on solutions and product development.

The Sr. Manager Data Engineering & Analytics will define data strategy, build scalable data platforms, and lead a multidisciplinary data team to enhance data quality and governance.

Lead and scale the data analytics function, manage a distributed analytics team, deliver actionable insights, and oversee analytics projects.

The Manager of Data Analytics Engineering will lead a team of engineers, manage data pipelines migration, collaborate with project managers, and mentor staff while fostering growth in a data-driven environment.

Lead a team of Data Scientists and Analysts, developing AI and data-driven solutions, driving analytics insights, and fostering collaboration across teams.

Lead a data science team to develop insights from autonomous vehicle data, create scalable platforms for data access, and collaborate with cross-functional teams on performance measures.