Top Senior Data Management Jobs

Lead a team to build repeatable reports, dashboards, and scorecards; ensure data integrity; provide BI support; collaborate with cross-functional stakeholders; design and manage A/B and multivariate tests; manage project communications and deliverables.

Provide technical leadership for Data Engineering and Systems Integration on Microsoft Fabric/Azure. Define data warehouse and ELT standards, data modeling, governance, and integration architecture for Shopify Plus and SaaS platforms. Lead and mentor a DBA, Data Engineer, and Integration Engineers, review technical designs, optimize platform resources, and act as technical escalation for complex integration and data flow challenges.

Lead master data management governance, define standards and mappings, approve data changes, audit mappings, manage a team of mapping specialists, collaborate with stakeholders, and drive MDM project delivery and training.

Manage and lead a team of data engineers, oversee data pipeline development, ensure data quality, and support analytics initiatives in financial services.

The Master Data Manager leads master data strategy and governance, ensuring data quality and compliance across the organization, while managing a team and engaging stakeholders.

Lead architecture and delivery of Radiant's enterprise data platform and AI strategy. Own vendor evaluations for secure AI tooling, mentor engineers, coordinate with software teams, ensure Databricks-based integrations and dashboards meet ITAR/EAR compliance, and act as a hands-on technical leader.

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.

Lead and grow a team of data engineers and analysts, own the data platform roadmap, design and operate reliable data pipelines across streaming, APIs, and various stores, set on-call and production monitoring practices, remain technically hands-on, and drive cross-functional collaboration to deliver analytics and infrastructure work.

Manage delivery of complex data pipelines in a hands-on role, leading a team of data engineers to develop scalable data solutions and improve analytics capabilities.

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.

Manage biographical data integrity for AA&D CRM (Advance): oversee scheduled data projects (graduation conversions, NCOA, voter files), design batch imports/exports, run data cleaning and QA, build queries/reports with SQL and BI partners, test changes, supervise one direct report, and collaborate across teams to improve processes and leverage AI/RPA for efficiency and accuracy.

The Data Manager oversees the full lifecycle of critical data, ensuring high-quality integration and analytics. Responsibilities include data operations, assessment of sources, collaboration with developers, and support for rapid-prototype phases.

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

Lead delivery pods for enterprise data governance and ADS architecture: design target-state ADS, document data lineage, implement aggregation-layer controls, conduct SME interviews, translate policy into delivery plans, manage analysts, select governance tooling, and report KPIs to senior stakeholders.

This role leads the development of consumer data models and AI reporting solutions, ensuring data consistency and governance while enabling self-service analytics across the organization.

Design and maintain Looker/LookML data models and dashboards, perform end-to-end SQL analysis, ensure data quality with Data Engineering, build predictive models, and translate findings into actionable recommendations for cross-functional stakeholders.

The role involves leading a team of analytics engineers to develop scalable data solutions for product metrics, ensuring data integrity, and fostering a culture of excellence in data-driven decision making.

Lead development and improvement of quality systems in manufacturing and lab operations; oversee data integrity, validation, and quality relationships with suppliers.

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

Lead a team of data scientists to enhance patient experiences through data insights, predictive modeling, and analytics for healthcare solutions.

This role involves leading a team in managing the CCC data platform, overseeing database engineering, vendor relationships, and operational objectives while leveraging AI to enhance efficiency.

The Data Product Manager will lead cross-functional teams to create high-impact data products, translate business needs into technical requirements, and manage product roadmaps. Responsibilities include collaborating with stakeholders, optimizing product performance, and ensuring compliance with industry standards.

Lead enterprise Procure-to-Pay data initiatives, governance, and quality across Global Supply Management. Manage Data Analysts, analyze source systems (ERP, planning, WMS, shop floor), drive root-cause analysis, data migrations, validations, and process improvements to ensure accurate master and transactional data supporting planning, logistics, manufacturing, and digital transformation.

Lead and manage a team of analytics professionals to deliver data-driven insights, manage analytics projects, collaborate with stakeholders, and provide actionable recommendations using statistical analysis, predictive modeling, and data visualization.

Lead a small data engineering team while contributing hands-on to design, build, and maintain production data pipelines, warehouse, ETL, and BI stack. Own data reliability, governance, reporting (internal and actuarial), enable self-service analytics, consolidate analytics standards, and drive infrastructure/vendor decisions aligned to business goals.