Data Governance Analyst

Oncology Nursing Society• US,

4d•$80,024 - $98,030•Remote

About The Position

The Data Governance Analyst is responsible for operationalizing and sustaining ONE’s data governance framework. This role ensures that enterprise data is discoverable, well defined, protected, and used consistently across platforms and teams. The Data Governance Analyst serves as the central executor of data governance practices, leveraging enterprise data governance, cataloging, metadata management, and analytics technologies to implement metadata management, data classification, access controls, lineage, and data quality monitoring. The role enables and coordinates business data owners, data stewards, analytics teams, and technology teams to work confidently with trusted data while ensuring governance is embedded into daily operations and system design. This is a full-time REMOTE (work-from-home) position. Occasional travel to the ONS Headquarters in Pittsburgh, PA throughout the year will be required.

Requirements

Strong understanding of data governance, metadata management, data lifecycle management, and stewardship models
Strong analytical and problem-solving skills, including the ability to synthesize complex business and technical data, identify root causes, troubleshoot issues, and recommend scalable solutions
Strong interpersonal and communication skills, with the ability to explain technical concepts, data risks, and governance requirements to non-technical stakeholders, business leaders, and executive leadership
Hands-on experience with enterprise data governance, cataloging, metadata management, analytics, and cloud data platform technologies
Proficiency in SQL for data profiling and validation
Comfort operating in evolving environments where governance must scale alongside analytics and AI adoption
Experience supporting data governance in cloud-based analytics environments
Experience working across cross-functional teams to translate business needs into governance requirements and technical actions
Familiarity with regulated data handling, classification, sensitivity labeling, retention practices, or audit support
Experience enabling governance adoption through stakeholder training, documentation, and data literacy support

Nice To Haves

Experience working with AI-enabled tools, automation, or data-driven AI use cases in an enterprise environment
Experience working in data warehouse or enterprise reporting environments
Experience supporting governance, quality, or metadata management across multiple third-party system integrations
Experience working in the Microsoft ecosystem including Azure, Fabric, and Purview.

Responsibilities

Operates and maintains the organization’s data governance framework, translating governance decisions into enforceable technical and process controls.
Serves as the day to day owner of data governance execution, ensuring governance activities are consistent, repeatable, and measurable.
Configures, manages, and optimizes data catalog and metadata scanning across SQL databases, data lake environments, analytics platforms, and integrated third-party systems.
Ensures data assets are cataloged, classified, and updated as systems evolve.
Builds and maintains the enterprise business glossary in partnership with business Data Owners and Data Stewards.
Develops and maintains end to end data lineage to support transparency, analytics trust, and impact analysis.
Ensures critical data elements are clearly defined, discoverable, and consistently referenced.
Implements and maintains data classification rules and sensitivity labels for PII and/or other regulated data.
Partners with IS Operations and Security to ensure labels, retention policies, and access rules are enforced across platforms.
Supports audits and risk reviews by providing evidence of data classification and protection controls.
Defines data quality rules and thresholds in collaboration with Data Owners and analytics teams.
Monitors data quality metrics for critical data elements and surface trends, risks, and remediation needs.
Enables teams to incorporate data quality checks into analytics pipelines and reporting workflows.
Develops and coordinates validation and testing approaches for governed data assets, including support for unit, integration, and user acceptance testing, to ensure data accuracy, integrity, and readiness for operational and reporting use.
Identifies root causes of data quality issues, including user errors, process breakdowns, and inconsistent interpretation of data definitions, and coordinates corrective actions including user retraining and process clarification.
Collaborates with Program Managers, project teams, and BI/engineering teams to embed data governance early in system implementations and data initiatives.
Ensures new data sources, integrations, and analytics assets meet governance standards before production use.
Partners with business stakeholders to support data ownership and stewardship responsibilities without owning the data itself.
Partners with department leaders and business users to gather data, reporting, and governance requirements and translate them into clear functional requirements, business rules, and technical specifications for analytics and development teams.
Provides guidance and enablement on how to use governance tools and standards effectively.
Designs and delivers ongoing data governance training and enablement for business stakeholders, including education on data definitions, metrics, data quality expectations, and appropriate use of governed data assets.
Partners with business users to reinforce data literacy, promote consistent interpretation of enterprise data, and support adoption of governance standards over time.
Acts as a trusted advisor on data governance practices, not as a gatekeeper.
Provides regular reporting to the Director of Information Services on governance KPIs, including catalog coverage, classification status, data quality trends, and compliance risks.
Reports data governance findings, risks, policy exceptions, and required corrections to assigned Data Owners within each business domain.
Facilitates discussion and decision‑making with Data Owners regarding data definitions, quality thresholds, remediation priorities, and acceptable risk, while tracking decisions and outcomes to ensure governance issues are resolved and documented.
Applies strong analytical thinking surfacing governance gaps early and recommends corrective actions.