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# Data Governance Specialist Role

- **Company:** Open Data Watch, Inc.
- **Location:** Washington, DC, United States
- **Contract:** Permanent contract
- **Skills:** Data Governance, Metadata, Open Data Protocol, Data Strategy, Data Management
- **Published:** August 7, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=fc21f1c724ca6e73

## About the Role

* Experience designing or operating data-governance, stewardship, or data-management programs.
 * Ability to define data standards, policies, decision rights, metrics, and issue-management processes.
 * Working knowledge of data quality, metadata, inventories, lineage, and lifecycle concepts.
 * Experience facilitating cross-functional governance forums and communicating with technical and business stakeholders.
 * Ability to align governance practices with federal data strategy, organizational risk management, and applicable requirements.

Requirements

What openings may require

Some openings may focus on enterprise governance design, while others may emphasize data quality, records, open data, master data, or specific governance platforms. Federal roles may seek familiarity with the Federal Data Strategy and agency responsibilities for inventories, metadata, standards, and data leadership.

## Description

Data Governance Specialists establish the decision rights, policies, standards, roles, and measures that help an organization manage data as a strategic asset. They turn broad expectations for quality, stewardship, access, lifecycle management, and accountability into operating practices that people can follow.

The work is organizational as well as analytical. Specialists convene data owners and stewards, define issue-management and escalation paths, measure adoption and data quality, and maintain the governance operating model as mission needs change. They do not own every catalog record or recurring data operation; they set the framework through which those activities are accountable and measurable.

What you'll build

 * Data-governance charters, policies, standards, and decision-rights models.
 * Stewardship structures, governance forums, issue-management workflows, and escalation paths.
 * Data-quality rules, metrics, exception processes, and improvement plans.
 * Accountability models that connect data owners, managers, inventory leads, metadata specialists, and technical teams.
 * Governance processes for AI system and data risk when the organization uses those systems.

Who you are

You can turn a policy goal into a practical operating model. You bring stakeholders together, make ownership visible, and use evidence to improve adoption instead of treating governance as a document-writing exercise.

You are comfortable at the intersection of data, technology, risk, and mission. You explain why a standard matters, where it applies, and how teams can meet it without losing sight of the work the organization must perform.


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