Data Governance Analyst

About the role

The Data Governance Analyst supports the Genworth Data Governance program (DGPO) by operationalizing governance standards, managing metadata and data quality workflows, and collaborating with business stewards to ensure that critical data assets are well-defined, trusted, and fit for use. This role operates within a modern cloud-native environment, leveraging Databricks/Unity Catalog for data engineering and Acryl DataHub as the enterprise data catalog.

Responsibilities

• Support data stewardship activities across assigned business domains, partnering with data stewards and subject matter experts to define, document, and maintain critical data elements and business glossary terms.
• Monitor and manage data quality issues by tracking DQ findings, coordinating remediation efforts with data owners, and escalating systemic issues through appropriate governance channels.
• Facilitate governance workflows including metadata review cycles, steward sign of, and CDE validation to ensure data assets meet standards.
• Maintain governance documentation and artifacts such as data dictionaries, domain taxonomies, RACI matrices, and policy standards, keeping them current as business needs evolve.
• Collaborate cross-functionally with business stakeholders, data engineering, and analytics teams to champion data governance adoption, support data literacy initiatives, and drive accountability for data quality at source.

Qualifications

• Bachelor's degree in a technical/analytical field; non-technical degrees considered with strong technical experience.
• 2–4 years of experience in data governance, data management, data quality, or a closely related analytics or data operations role.
• Hands-on experience with at least one enterprise data catalog platform (Acryl Datahub, Collibra, Alation, Informatica, or equivalent).
• Working knowledge of SQL for data querying, profiling, and validation in a cloud or warehouse environment (Databricks, Snowflake, Redshift, or similar).
• Demonstrated ability to write clear, concise business definitions for data attributes and data elements.
• Experience contributing to or executing data quality monitoring, issue tracking, and remediation workflows.
• Strong written and verbal communication skills; comfortable presenting findings and facilitating working sessions with business stakeholders.
• Ability to manage multiple concurrent workstreams with attention to detail and follow-through.
• Good working knowledge of SDLC and Agile Methodologies (mainly Kanban and Scrum).
• Interest in learning and using new technologies.