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OpenDataJobs
Washington, DC, US
Source: OpenDataJobs careers · View original posting
From OpenDataJobs's posting. “We” and “our” refer to the employer.
The work
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.
· 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.
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.
Organizations using AI may need governance practitioners who can define clear accountability, inventories, review processes, and monitoring for system and data risks. The National Institute of Standards and Technology's (NIST) Artificial Intelligence Risk Management Framework (AI RMF) organizes this work around Govern, Map, Measure, and Manage functions, but it does not replace the organization's own decision rights.
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