Data Governance Analyst
Location: Richmond, Virginia
Experience: 10+ years
Hybrid - Onsite 2 days a week
Terms : 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.
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 several of the following technologies is preferred:
- AWS, S3, Glue, Glue Data Catalog, and Lake Formation
- Snowflake
- Python and SQL
- Power BI
- SharePoint
Experience in healthcare, behavioral health, Medicaid, or with government is highly desirable.
Key Responsibilities
Data Governance
- 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.
Metadata Management
- 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.
- Support metadata ingestion into the enterprise metadata repository.
Data Quality
- Define business data quality rules.
- 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.
Data Lineage & Architecture
- 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.
Enterprise Data Platform
- 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.
Reporting & Communication
- 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.
Desired Knowledge & Skills
Strong knowledge of Enterprise Data Governance, Data Stewardship, Metadata Management, Data Catalogs, Data Quality Management, Master Data Management, Business Glossaries, Critical Data Elements, Data Classification, Data Lineage, Information Lifecycle Management, Cloud Data Platforms, Operational Data Stores, Data Warehousing, and AI-ready data governance.
The ideal candidate is highly organized, analytical, collaborative, and self-motivated, with strong facilitation skills and the ability to translate business requirements into practical governance artifacts. A passion for improving enterprise data quality and governance is essential.