Top Senior Data Management Jobs

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.

Lead agile software development and data integration efforts, respond to audits/RFPs, enforce data governance, write and review code, troubleshoot and root-cause issues, deliver data visualizations to senior management, and manage/mentor a team while aligning IT solutions to business strategy.

Manage and secure the organization's data operations: administer and optimize relational databases, maintain Tableau dashboards, lead offshore DBAs/analysts, ensure HIPAA-compliant backups/recovery, support ETL/data ingestion pipelines, automate routine tasks, and collaborate with developers and data engineers to improve performance and data integrity.

Manage supplier master data governance by defining policies, controls, and standards; lead data quality, compliance, and remediation efforts; partner with business and IT for UAT and system implementations; oversee a data governance team, documentation, metrics, and cross-functional process improvements to ensure data integrity and audit readiness.

Own developer relations for GPU-accelerated analytical data processing: integrate NVIDIA libraries into query engines and OLAP databases, produce rigorous benchmarks, create reference integrations and guides, collaborate with engine architects and NVIDIA product teams to define APIs and roadmap, and drive adoption across open source and commercial projects.

Lead planning, execution, and delivery of large enterprise data and analytics projects. Manage project life cycle, risks, budgets, vendors, stakeholders, and cross-functional teams. Enforce PM best practices, create WBS, produce status/KPI reports, mentor team members, handle escalations and on-call support, and drive process improvements and project closures.

Manage and develop the division's GIS, enterprise databases, asset inventory systems, and Microsoft-based solutions. Lead data governance, BI dashboards (Power BI), field data collection, drone/UAS mapping, and emerging sensor technologies. Supervise technical staff, coordinate with IT and vendors, support grant/compliance reporting, and drive technology strategy for Parks and Natural Resources.

Lead implementation of a data governance strategy and roadmap for consolidating source systems into a centralized data warehouse. Define master data, business rules, reference data, and data stewardship processes; publish policies; improve data workflows and quality; enable BI/analytics and provide technical leadership to Tech Ops.

Lead solution/data architecture for end-to-end enterprise data warehouse implementations including data integration, ETL, data marts, reporting, cubes and MDM. Design architectures using frameworks (Zachman/TOGAF), guide implementation teams, and apply healthcare payer domain expertise. Work with Oracle/DB2/SQL Server and major ETL/BI tools to deliver large-scale reporting and analytics solutions.

Lead implementation of end-to-end global data governance for domain areas (Product, Customer, Vendor). Run governance council, map data ownership, apply COBIT, drive change management and adoption, create roadmaps and scorecards, prototype and test solutions, represent data governance with cross-functional partners and AI governance, promote data literacy, and manage Precisely Automate Studio and ArcGIS licensing.

Manage a team delivering accurate, timely data reporting for Transfer Agency clients. Build advanced Excel data models (Power Pivot, DAX, Power Query), automate reporting, develop dashboards and KPIs, ensure data quality and governance, and support process improvement and stakeholder reporting needs.

The role involves leading the data governance team, managing IT projects, collaborating with stakeholders, and ensuring continuous improvement of processes. Responsibilities include strategic planning, client management, and optimizing resource utilization, while overseeing governance activities and departmental management.

Lead a team of BI/data developers to build and maintain data models, dashboards, and analytics solutions (Power BI, SQL, Synapse). Drive data governance, partner with stakeholders and security teams, present to leadership, and promote data-driven decision making across the firm.

Lead marketing data automation and reporting efforts: build and maintain Power BI dashboards, automate reporting, integrate marketing and insights data, support AI data-readiness, and partner with Marketing, Finance, and Insights to deliver actionable analytics for planning and post-event analysis.

Lead and manage BI and Big Data projects with strong project management, AWS, Datastage and DB2 expertise. Collaborate in a global delivery model, apply analytical skills, communicate with stakeholders, and deliver enterprise data solutions.

Lead data governance activities including policy, retention, access, quality, and audits. Drive CEDS implementation, oversee external data requests and training, manage master data calendar, support budgeting, reporting and strategic planning, and maintain the Office of Data Governance website while coordinating with stakeholders and governance boards.

Lead development and implementation of a companywide data governance program: define governance standards, data definitions, business and quality rules, and data accountability. Manage business participation, review and improve operational processes, ensure effective management controls, lead engagements, present findings to senior management, and maintain enterprise documentation in coordination with SVP/VP stakeholders.

Lead design and delivery of metadata-driven ETL pipelines and cloud-native data solutions. Build PySpark/Informatica IICS frameworks, implement Data Vault 2.0 models on Snowflake/AWS, improve data quality and operating model, integrate analytics teams, and support actuarial data use in insurance projects.

The Senior Manager, Data & Analytics designs and implements data solutions, manages projects, and partners with clients to drive transformation initiatives using analytics and AI/ML.

Lead and mentor a data engineering team, define technical vision and strategy, oversee data pipeline design, and collaborate with cross-functional teams.

Lead analytics and insights for Vendor Management by delivering advanced reporting, decision-support analyses, and scalable data solutions. Own data platform reliability, governance, ETL pipelines, semantic layers, and self-service reporting (Tableau/Power BI). Partner with stakeholders and technology teams to translate requirements, automate data curation, and produce executive summaries that drive vendor management decisions.

As a Senior Data Engineer, you will design and maintain data infrastructure, implement ETL processes, and optimize data workflows using Python and PySpark.