Top Data Management Jobs in Richmond, VA

The role involves driving strategy through data analytics, leading a team, implementing process improvements, and developing data models. Requires strong analytical, problem-solving, and leadership skills.

Lead enterprise validation of analytical tools for the card business: design and execute validation projects, assess tool methodologies and risks, prototype best practices, communicate results, manage multiple projects, and mentor junior staff.

The Senior Manager, Data Analysis will validate business impacting analytical tools, assess methodologies, coach junior staff, and execute validation projects.

The Manager will lead payments governance and oversight initiatives, implement data reporting frameworks, and enhance risk management practices through stakeholder collaboration and data insights.

Lead the migration domain to ensure accurate, complete, repeatable migration of customer, account, product, and transactional data. Oversee migration automation/tooling and legacy data hygiene. Own analytical frameworks, data mapping, and reconciliation controls to ensure institutional and regulatory confidence. Lead cross-functional teams and drive product outcomes aligned with business and technology objectives.

Lead design and rollout of a fit-for-purpose data governance program: manage data lifecycle, implement governance frameworks and tools, drive data catalogs/lineage, upskill stewards, define KPIs, and partner cross-functionally to improve data quality, compliance, and usability.

Lead and mentor a team of analysts to deliver HR-related analytics and BI solutions. Mine and model large datasets, design tests, improve reporting and operational efficiencies, and collaborate across business units to inform strategy and product decisions.

Lead data governance for the Global Payment Network: implement and enforce policies, ensure data quality, master data management tooling, drive automation and process improvements, collaborate with executives, data stewards and tech teams, and synthesize risk reporting and insights for senior leadership.

Lead validation of enterprise analytical tools: refine validation framework, plan and execute projects, assess methodology quality and risk, prototype best practices, communicate findings, and coach junior staff.

Lead a team delivering enterprise-wide model risk reporting and AI-driven automation. Build and deploy scalable ML/AI solutions, conversational reporting, multi-agent workflows, and centralized data integrations. Drive analytics strategy, validate models and data, improve reporting and operational efficiency, and collaborate across business units.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Serve as a second-line data risk advisor by validating enterprise analytical tools, conducting risk and gap assessments, influencing stakeholders, designing controls, leading validation projects, mentoring staff, and ensuring data management practices meet regulatory and enterprise risk standards.

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.

The Senior Manager will lead cross-functional analytics projects, validate analytical tools, and mentor junior staff while driving data-based business strategies.

The Senior Manager of Data Analysis will manage validation projects, assess analytical tool risks, and mentor junior staff while collaborating cross-functionally and enhancing analytical capabilities.

Lead and grow a data platform engineering team to build and maintain a petabyte-scale data lake and infrastructure. Drive platform roadmap, scale systems globally, collaborate cross-functionally, and embed best practices for security, privacy, and AI transformation.

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

Lead development and implementation of data governance strategies, manage client accounts and deliverables, supervise and mentor teams, analyze data to inform business decisions, ensure compliance with firm standards, and identify improvements in data management processes.

Lead development and execution of data-driven strategies, manage project planning and delivery, mentor and coach team members, ensure quality and ethical standards, design cloud data architectures and governance frameworks, analyze complex datasets to produce actionable insights, and drive continuous improvement using advanced analytics and modern data technologies.

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Lead and manage delivery of modern data ecosystems and managed data analytics programs. Oversee project planning, budgeting, quality, and client accounts. Mentor teams, drive data strategy, convert insights to business opportunities, and ensure standards and risk management across large transformations.

Lead a team of analysts to drive strategy through data mining, modeling, and BI. Work with massive datasets, design/validate tests, improve reporting/processes, consult on data systems, and collaborate across business units to enhance customer experience.

Lead data strategy, architecture, and modeling for high-volume transactional network platforms. Build monitoring and anomaly-detection frameworks, optimize operational data schemas, align local assets with enterprise data strategy, communicate findings to stakeholders, and mentor technical staff.

The Manager, Data Analysis will lead a team of analysts, leveraging analytical skills and models to drive data strategy and improve customer experiences. Responsibilities include mining complex data, enhancing operational efficiencies, and mentoring junior team members while collaborating across business units.