Data Governance Analyst

Location: Richmond, Virginia. Experience: 10+ years. Hybrid – onsite 2 days a week. Term: 9 to 12 months with possible extensions. Interview process: video & in‑person.

About the Role

We are seeking an experienced Data Governance Analyst to support the implementation of an Enterprise Data Governance Program. This role will work closely with Data Owners, Data Stewards, Business Owners, Enterprise Architecture, Data Engineers, Project Teams, and Information Security to establish trusted, governed enterprise data for operational and analytical use cases. The position focuses on governance activities supporting enterprise data ingested into the AWS Data Platform and consumed through Snowflake. The successful candidate will help establish governance processes, metadata, business rules, data quality standards, and stewardship practices while supporting a growing enterprise data platform.

Key Responsibilities

• Support implementation of the Enterprise Data Governance Program.
• Facilitate governance workshops with business stakeholders.
• Support onboarding of new applications into the governance program.
• Partner with Data Owners and Data Stewards to establish governance for new enterprise datasets.
• Develop and maintain governance policies, standards, procedures, and supporting documentation.
• Capture and maintain business metadata, technical metadata, and data dictionaries.
• Develop and maintain the Enterprise Business Glossary.
• Define and document Critical Data Elements (CDEs).
• Map business metadata to technical metadata and support metadata ingestion into the enterprise metadata repository.
• Define business data quality rules and support data profiling and business validation activities.
• Monitor data quality metrics and trends; assist Data Stewards with remediation planning; perform reconciliation and validation across enterprise data sources.
• Document business and technical data lineage and end‑to‑end data flows; assist with impact analysis for new data sources.
• Support governance activities across Bronze, Silver, Gold, Operational Data Store (ODS), and Analytical Data Store (ADS) layers.
• Collaborate with Data Engineers supporting Python‑based AWS data pipelines.
• Support governance of enterprise datasets published to Snowflake.
• Assist with proof‑of‑concept initiatives to consolidate data from multiple source systems into governed enterprise data assets.
• Support Information Lifecycle Management (ILM), data classification, retention, and internal data sharing processes.
• Produce governance dashboards and metrics; prepare executive presentations and governance reports.
• Present recommendations to governance committees and project teams; communicate governance requirements to business and technical audiences.

Required Qualifications

• Minimum of 10 years of experience in Data Governance, Data Management, Data Quality, Business Analysis, Metadata Management, or related disciplines.
• Experience implementing enterprise Data Governance programs.
• Experience facilitating governance workshops with business and technical stakeholders.
• Strong SQL skills for data analysis and validation.
• Experience documenting metadata, business glossaries, and data dictionaries.
• Experience defining business rules and Critical Data Elements (CDEs).
• Experience performing data profiling, reconciliation, and validation.
• Excellent written and verbal communication skills.

Preferred Experience

• Experience with AWS services such as S3, Glue, Glue Data Catalog, and Lake Formation.
• Experience with Snowflake.
• Python and SQL development.
• Power BI.
• SharePoint.
• Experience in healthcare, behavioral health, Medicaid, or government sectors.

Desired Knowledge & Skills

• Enterprise Data Governance and Data Stewardship.
• Metadata Management and Data Catalogs.
• Data Quality Management and Master Data Management.
• Business Glossaries and Critical Data Elements.
• Data Classification, Data Lineage, and Information Lifecycle Management.
• Cloud Data Platforms, Operational Data Stores, Data Warehousing, and AI‑ready data governance.
• Highly organized, analytical, collaborative, and self‑motivated with strong facilitation skills.
• Ability to translate business requirements into practical governance artifacts.
• Passion for improving enterprise data quality and governance.