Top Senior Data Management Jobs in Richmond, VA

Manage data analytics for PULSE Risk & Compliance by analyzing large datasets, identifying transaction anomalies and risk exposure, validating models, improving reporting and processes, and supporting compliant data strategies. The role involves Python-based programming, BI, database and data-storage design, strategic testing, cross-functional collaboration, project leadership, and people management in a hybrid environment.

Leads enterprise-wide validation of analytical tools, including planning validation projects, assessing methodology quality and tool risk, researching best practices, and communicating findings through reports and presentations. Partners cross-functionally to influence business strategy, handles concurrent projects, develops solutions to business problems, and coaches junior staff. The role requires substantial data analysis, statistical or econometric modeling, large-scale data manipulation, open-source technology experience, and people management.

Leads data analytics strategy, modeling, testing, reporting, and process improvements across business units. Mines complex databases, evaluates products and processes, improves operational efficiency, and consults on data systems. Manages and mentors junior analysts while supporting projects through the full lifecycle. The role emphasizes business intelligence, programming, strategic analysis, and collaboration in a fast-paced environment.

Leads data analysis strategy, modeling, testing, reporting, and process improvements using large-scale databases. Manages and mentors junior analysts, evaluates products and marketing initiatives, improves operational efficiency, consults on data systems, and collaborates across business units. The role requires strong programming, business intelligence, communication, leadership, and project management skills.

Leads enterprise analytical tool validation, assessing methodology quality, risk, technical issues, and business impact. Plans validation projects, researches emerging practices, develops solutions, communicates findings through reports and presentations, and mentors junior staff. The role requires extensive data analysis, statistical or econometric modeling, open-source data technology experience, data governance knowledge, predictive analytics expertise, and people management.

Leads data analysis and data product initiatives involving large databases, modeling, testing, reporting, process improvements, and product analytics. Manages and mentors junior analysts, partners with technology and business teams, supports data-system design, and develops strategic tests for products and marketing materials. Requires strong analytical, programming, business intelligence, communication, and leadership skills.

Lead data analytics strategy, mine and analyze large-scale datasets, build and validate models, improve reporting and operational processes, evaluate products and marketing initiatives, and consult on data systems. Manage and mentor junior analysts, collaborate across business units, oversee concurrent projects, and apply business intelligence tools to support customer experience and organizational decision-making.

Leads enterprise data analysis and analytical tool validation initiatives for card data products. Responsibilities include developing validation frameworks, planning validation projects, assessing methodology quality and risk, researching emerging analytical tools, prototyping best practices, preparing reports and presentations, and coaching junior staff. The role requires collaboration with data product and technology partners, independent problem solving, and management of concurrent projects.

Leads Enterprise Supplier Management analytics strategy, data product development, analytical tool validation, and data ecosystem improvements. Partners with senior leaders, Product, Technology, Risk, and Operations teams to evaluate business models, manage strategic priorities, assess analytical tool risk, and develop insights. Oversees and mentors a team of at least four Data Analysts while communicating findings through validation reports and presentations.

Manage data governance and risk programs for Global Payment Networks. Analyze large datasets, build and validate models, improve data and reporting processes, establish controls, support privacy and regulatory compliance, and lead cross-functional projects. The role also includes mentoring junior analysts, managing concurrent initiatives, and consulting on data systems, product testing, and business intelligence solutions.

Leads enterprise compliance testing analytics, tooling strategy, and analytical projects. Partners with engineering, data science, legal, compliance, risk, and executive stakeholders to identify and mitigate compliance risks. Evaluates analytical tools, researches emerging practices, communicates findings through reports and presentations, and mentors junior staff. The role requires advanced data analysis, statistical or econometric modeling, large-scale data manipulation, data governance, and people management experience.

Leads data engineering architecture and modeling initiatives, designing scalable pipelines, cloud data platforms, and reusable data solutions. Collaborates with engineering, product, analytics, and data science teams while mentoring developers and establishing common design patterns. Responsibilities include distributed data processing, relational and NoSQL systems, data security, observability, streaming pipelines, and operational excellence across platforms such as Databricks and Snowflake.

Analyze large-scale data, build and validate models, improve processes and reporting, evaluate products and marketing initiatives, and consult on data systems. The role requires programming, strategic analysis, collaboration across concurrent projects, and leadership in a hybrid environment.

Leads large-scale data engineering initiatives for Risk Tech, designing and delivering scalable cloud data platforms, pipelines, and applications. Responsibilities include architecture, data modeling, distributed processing, cloud warehousing, AI-enabled risk solutions, platform evaluation, operational resilience, and technical mentoring. The role collaborates with product managers, software engineers, analysts, and data scientists while independently driving architectural decisions and communicating technical outcomes to stakeholders.

Leads enterprise analytical-tool validation, including framework refinement, project execution, methodology risk assessment, technical research, prototyping, and validation reporting. Partners with cross-functional leaders to influence business strategy, solves complex analytical problems, and coaches junior staff. Requires substantial data analytics, open-source technology, statistical modeling, and people-management experience.

Leads people analytics initiatives that support talent strategy and workforce decisions. Responsibilities include developing analytics frameworks, managing data projects, building AI-powered data products and self-service tools, analyzing workforce data, prototyping automation solutions, and delivering insights to HR stakeholders and senior leaders. The role also involves data strategy, dashboard development, project execution, and potentially people management.

Manages data governance and pricing-related risks by overseeing processes, controls, reporting, documentation, and improvement initiatives. The role analyzes process data, identifies gaps, resolves policy-related issues, collaborates on enterprise projects, represents departmental interests, and trains junior staff and internal stakeholders. Responsibilities include maintaining procedures and diagrams, recommending process changes, supporting executive reporting, and ensuring adherence to data management and governance frameworks.

Senior Data Manager acquires, validates, integrates, protects, and manages enterprise data throughout its lifecycle. The role develops ETL solutions, data architectures, models, stored procedures, reporting datasets, and visualizations using Databricks, SQL, and cloud technologies. Responsibilities include translating business needs into technical requirements, leading data projects through deployment, analyzing complex data, improving processes, and supporting business decisions through accessible insights.

Manages business intelligence, data analysis, reporting, data governance, funding controls, and ERP-related initiatives for financial and grants management. Integrates data from financial, payroll, inventory, timekeeping, and payment systems; develops dashboards, metrics, forecasts, and federal and non-federal reports. Provides recommendations supporting budgets, capital funding plans, grant compliance, agency investments, and strategic decision-making. Requires collaboration with technical and nontechnical stakeholders.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, campaign reporting, experimentation, and lifecycle analysis. Partners with Marketing and Finance to connect performance metrics to business goals, automate reporting, and generate actionable insights. Builds churn, retention, segmentation, and LTV models while evaluating paid acquisition and customer growth opportunities using SQL, Python, BI tools, marketing platforms, and modern AI-enabled workflows.

Leads the design, delivery, and optimization of data architecture, pipelines, semantic layers, data quality frameworks, and Tableau BI platforms. Partners with stakeholders to manage requirements, project plans, sprint execution, monitoring, governance, and release delivery. Guides data engineers, manages team members, and supports AI-enabled analytics capabilities. Requires strong SQL, Spark, PySpark, SSIS, cloud data platform, CI/CD, Tableau infrastructure, and data engineering expertise.

Leads and grows the data engineering team while owning enterprise data architecture, ingestion, modeling, semantic layers, governance, secure APIs, and reliable platform outcomes. Partners with finance, operations, sales, marketing, and product to deliver governed, traceable data for products and AI agents. Sets the roadmap, manages vendors and costs, reviews architecture, contributes code, and delivers cross-functional data platform projects.

Lead Client Legal Services analytics strategy and team development. Own Power BI reporting products, Microsoft Fabric data solutions, governance, predictive modeling, responsible AI adoption, ROI measurement, and executive insights. Partner cross-functionally to improve legal operations, litigation outcomes, staffing, capacity, cost management, quality, and workflow optimization while building scalable analytics capabilities and institutional knowledge.

Lead and grow a global data engineering team while establishing foundational data platforms and engineering standards. Design and oversee GCP-based pipelines, medallion data models, DataOps, monitoring, SLAs, CI/CD, governance, and data quality practices. Drive AI adoption across engineering workflows and build reliable, AI-ready data. Partner with business and technology stakeholders to prioritize roadmaps, deliver scalable solutions, and support data democratization.

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.