Sr Data Governance Analyst

ExecRecruitment•Richmond, VA

About The Position

The Senior Data Governance Analyst supports implementation and continuous improvement of enterprise data governance through the integration of people, processes, and technology. The role collaborates with data owners, data stewards, and enterprise partners to translate governance policies, standards, and decisions into repeatable, sustainable, and measurable business processes embedded in operations and technology delivery. It emphasizes governance by design, business process improvement, stakeholder collaboration, operational accountability, and organizational adoption rather than hands-on technical development. The analyst applies business analysis and facilitation skills to complex business and data management challenges, interpret policies, elicit requirements, facilitate cross-functional decisions, and translate governance needs into practical solutions. The role may lead or support prioritized initiatives in governance decision processes (Awareness, Risks, Issues, and Decisions—ARID), access governance, data sharing, automated data onboarding, Enterprise Master Person Index (EMPI) and reference data management, data quality improvement, compliance reviews, and data product requirements.

Requirements

Demonstrated experience in senior-level business analysis, requirements elicitation, business process improvement, and complex problem-solving.
Advanced facilitation skills, including leading cross-functional working sessions, navigating competing priorities, building consensus, and driving decisions to resolution.
Proven ability to analyze, design, document, and support implementation of sustainable business processes.
Ability to interpret policies, standards, and business requirements and translate them into practical operational processes, business rules, and controls.
Working knowledge of enterprise data governance concepts, including data ownership, stewardship, access governance, data quality, compliance, and data lifecycle management.
Strong analytical, communication, stakeholder management, and organizational skills, with the ability to work independently and collaboratively.
Five or more years of experience in business analysis, requirements elicitation, process improvement, or related enterprise business functions.
10 years of data analysis experience.
10 years of experience with data lineage or cataloging.
10 years of experience creating data policies or procedures.
10 years of SQL proficiency.
10 years of data warehouse experience.
10 years of requirements elicitation experience.
7 years of experience with databases, such as relational databases, SQL Server, Oracle, or Snowflake.

Nice To Haves

Experience supporting enterprise data governance initiatives, including governance process implementation, data stewardship, data quality, metadata, or access governance.
Experience in government, healthcare, or another regulated environment.
Familiarity with enterprise data integration, interoperability, master and reference data management, and governed data products.
Knowledge of data governance frameworks such as DAMA-DMBOK or DMMI and process improvement methodologies such as BPMN, Lean, or Six Sigma.
Familiarity with AWS, Snowflake, Commonwealth of Virginia/VITA standards, or relevant professional certifications such as CDMP.
A bachelor's degree in information systems, business administration, information management, or a related field is preferred; equivalent professional experience and relevant certifications may be considered.

Responsibilities

Analyze business processes and data management practices to identify governance gaps, risks, inefficiencies, and improvement opportunities.
Facilitate requirements elicitation, root cause analysis, and current-state and future-state process design for governance initiatives.
Translate governance policies, standards, business needs, and decisions into actionable business requirements, workflows, procedures, and operational controls.
Develop process maps, business requirements, standard operating procedures, RACI matrices, and performance measures to support governance implementation and accountability.
Support process implementation, automation, adoption, and continuous improvement to establish sustainable governance practices.
Facilitate cross-functional working sessions involving data owners, stewards, business units, enterprise architecture, engineering, security, analytics, and external partners.
Facilitate complex discussions, reconcile competing priorities, evaluate alternatives, and support informed governance decisions by authorized stakeholders.
Clarify governance decision rights, responsibilities, dependencies, and required implementation actions.
Document governance decisions, communicate requirements and outcomes to responsible teams, and coordinate follow-through to implementation.
Foster collaboration and accountability for consistent application of governance practices across business and technical stakeholders.
Support data owners and stewards in implementing governance policies, standards, roles, and responsibilities within operational processes.
Collaborate with data owners, stewards, and enterprise partners to define, document, and monitor measures of governance effectiveness, stakeholder engagement, compliance, and data quality.
Facilitate data quality issue identification, root cause analysis, remediation planning, and continuous improvement.
Support data access governance and data sharing processes by ensuring authorized decisions, requirements, and conditions are documented, communicated to execution teams, and tracked through implementation.
Collaborate with enterprise partners to embed governance requirements into data onboarding, integration, management, and consumption.
Elicit and document business and analytical requirements to help ensure governed enterprise data products meet consumer needs.
Lead or support prioritized initiatives involving ARID governance decision processes, access governance, data sharing, automated data onboarding, EMPI and reference data management, data quality improvement, compliance reviews, and data product requirements.