Staff Data Governance Administrator
New
H
Horizon3 AICybersecurity
US, RemoteFull-TimeStaff
SalaryBase salary range: $160,000 - $210,000 annually.
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Job Details
- Experience
- 7+ years
- Required Skills
- Project ManagementArtificial IntelligenceSalesforce
Requirements
- 7+ years of experience in Revenue Operations, Sales Operations, Business Systems, GTM Systems, or Data Operations roles.
- Proven experience leading data governance, data quality, or process transformation initiatives in a high-growth environment.
- Deep Salesforce expertise, including Sales Cloud administration, reporting, dashboards, automation, data architecture, and governance.
- Strong understanding of GTM business processes including lead-to-opportunity, forecasting support, quote-to-cash, customer lifecycle, and partner operations.
- Experience managing third-party firmographic data solutions and related data enrichment, matching, and governance processes.
- Demonstrated practical use of AI to help solve complex data governance and operational challenges.
- Strong project management and stakeholder management skills.
- Ability to influence cross-functional leaders without direct authority.
- Excellent documentation, communication, and change-management skills.
- Willingness to travel up to 15%.
Responsibilities
- Serve as the strategic administrator for GTM data governance across Salesforce and adjacent GTM systems.
- Define and maintain governance standards for accounts, contacts, leads, opportunities, and related revenue data objects.
- Establish business rules for field usage, required data, ownership, lifecycle stages, routing dependencies, and record hygiene.
- Partner with cross-functional leaders to translate business requirements into scalable data controls and operational policies.
- Design and maintain governance processes for deduplication, normalization, enrichment, validation, and exception handling.
- Improve end-to-end GTM workflows by reducing data friction across lead, opportunity, forecasting, customer lifecycle, and partner operations.
- Identify root causes of data quality issues and drive remediation through process change, automation, and user enablement.
- Partner with analytics and data teams to improve reporting accuracy, metric consistency, and executive visibility.
- Establish monitoring and audit routines for data quality, adoption, and policy adherence.
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