Top Senior Data Management Jobs in Washington, DC

Analyzes and visualizes Tech Refresh data for an Intelligence Community customer. Responsibilities include assessing data quality, identifying trends and patterns, preparing stakeholder reports, recommending automation and process improvements, supporting data governance, and collaborating with engineers, programmers, and management on system modifications and operational decisions.

Build and manage data ingestion, integration, transformation, modeling, and quality frameworks for federal financial management and IT programs. Analyze large datasets using SQL, Python, R, PySpark, and Databricks; develop predictive models and apply machine learning techniques. Ensure data governance and quality standards, define Databricks data quality metrics, support client meetings and documentation, and contribute to consulting and business development activities.

The Manager, Data Management leads a firm-wide data management program, ensuring data quality and accountability across master data domains while partnering with stakeholders and managing staff.

Conduct research and provide strategic advice on HR technology, data governance, HCM systems, and AI’s impact on HR. Develop thought leadership, market analysis, presentations, and client recommendations for CHROs and HR technology leaders. Track vendors and emerging technologies, support sales and conferences, review peer content, improve research processes, and mentor junior analysts. The role requires executive presence, strong analytical and communication skills, and collaboration with global clients, including at least 6–8 hours monthly supporting Asia-Pacific organizations.

Manage and administer authoritative databases and shared datasets, design data models, build ETL processes, enforce data quality, document data flows, optimize datasets for reporting and Power Platform, and support migrations, performance tuning, and data issue resolution.

Lead enterprise data governance, quality, MDM, cleansing, validation, reconciliation, and migration efforts to support ERP implementations and large transformation programs. Develop governance frameworks, coordinate data readiness and testing, produce executive reporting and presentations, manage project plans and governance artifacts, and drive stakeholder alignment and change management.

The Senior Director Analyst in MDM leads research and advisory functions, focusing on Master Data Management strategies and providing clients with actionable insights to enhance their data initiatives. This role requires strong analytical skills and the ability to communicate complex concepts effectively.

Perform data extraction, integration, profiling, and analysis across Molina systems and external sources. Produce data quality controls, KPIs, reports, and recommendations; support root cause investigations, ad hoc requests, and data governance initiatives.

Design, develop, maintain, and optimize enterprise Tableau dashboards and BI solutions. Integrate and cleanse data from Oracle/Sybase/Big Data, tune SQL, automate Tableau extracts, manage Tableau Server on Linux, support testing, UAT, deployments, and troubleshoot data integrity and performance issues.

Lead science data and knowledge management at Audubon, enhancing data accessibility and usage across various scientific programs while collaborating with IT and Conservation Teams.

Architect and deploy scalable Inventa data-management solutions, lead complex enterprise integrations (APIs, on-prem, cloud, SaaS, data lakes), resolve architectural performance and access issues, create global architecture guides and documentation, and feed product improvements through field insights. Customer-facing, cross-functional collaboration with Sales, Customer Success, and Product.

Lead development and execution of enterprise data management strategy, governance, and quality. Oversee MDM, metadata, data lineage, catalogs, lifecycle, profiling, cleansing, and compliance. Partner with engineering, analytics, and security to deliver reliable data platforms, KPIs, and mentor a data management team.

Lead integration of technology into information systems, design data warehouse and BI capabilities, define data architecture and dictionaries, centralize disparate data, design dashboards, document system architecture, perform data quality and management, and provide solution engineering, pilots, and enablement for analytics and resource management.