Senior Manager, Data Governance, Operations NA

Vantage Data Centers•Denver, CO

23d•$170,000 - $180,000•Hybrid

About The Position

The Operational Excellence team establishes the systems, governance, and capabilities that enable Vantage to operate at scale across North America with reliability, consistency, and speed. We strengthen the scalability and performance of NA Operations: Solutions Engineering, Design Integration, Mission Critical Operations, and Customer Experience- by partnering with leaders and global functions to execute the Operations Plan of Record, standardize operating models, drive process excellence, enable data-informed decisions, and embed disciplined transformation and continuous improvement. Operational Excellence at Vantage is hands-on and outcome-driven. We combine portfolio governance, systems thinking, operational rigor, and human-centered enablement to reduce friction, increase predictability, and accelerate performance. Our team members lead high-impact initiatives, shape cross-functional execution, and directly influence how Vantage delivers on its growth, operational reliability, and customer commitments. This role will be based in Denver, CO. Following our flexible work policy (3 days in-office, 2 days flexible). The Senior Manager, Operations Data Governance enables North America Operations to use data confidently and consistently to manage performance, identify risk, prioritize action, and improve operational outcomes. This individual contributor establishes and operationalizes the governance practices needed to ensure structured and unstructured Operations data is clearly defined, appropriately owned, reliable, traceable, and fit for purpose. The role works directly with Operations leaders, functions, data owners, and stewards to clarify accountability, standardize critical data and metric definitions, resolve quality issues, and embed governance into everyday business processes. It translates enterprise data standards into practical approaches that improve data trust and usability without creating unnecessary complexity for Operations. The role serves as a connective point across Operations, Operations Data & Intelligence, Global Data & AI, and technology teams, establishing feedback loops that translate operational needs, data issues, and user feedback into improvements to data definitions, controls, products, and source systems. The ideal candidate combines strong data-governance expertise with hands-on execution, business partnership, and the ability to drive cross-functional accountability and continuous improvement.

Requirements

Bachelor’s degree in data management, information systems, computer science, engineering, business, or a related field, or equivalent professional experience.
Five or more years of experience in data governance, data management, analytics, data products, or a related discipline.
Demonstrated experience implementing governance operating models, ownership and stewardship practices, business glossaries, data catalogs, and data-quality processes across the data and technology lifecycle.
Experience using catalog, metadata, lineage, data-quality, observability, AI-enabled, and workflow-automation tools to scale governance and reduce manual effort.
Hands-on experience with Microsoft Purview Unified Catalog and Data Map, or comparable platforms.
Strong knowledge of data ownership, stewardship, metadata, lineage, data quality, observability, and data- and AI-governance lifecycle practices.
Technical fluency in data models, semantic models, data flows, lineage, access controls, and information protection, including how these affect analytics and AI-enabled solutions.
Ability to translate enterprise policies and technical requirements into practical processes and scalable, AI-assisted or automated governance workflows.
Strong facilitation and influencing skills, including the ability to drive accountability without direct authority.
Strong analytical judgment and ability to resolve ambiguous ownership, definition, and quality issues.
Clear written and verbal communication skills, with the ability to make complex data concepts understandable and actionable.
Highly organized, proactive, and comfortable independently advancing work within a developing capability.

Nice To Haves

CDMP, DCAM/CDMC, or a relevant Microsoft Fabric, Power BI, data governance, or information-protection certification is preferred.
Microsoft Purview experience is strongly preferred, along with working knowledge of Microsoft Fabric, Power BI, and Power Platform.
Experience governing data used by AI-enabled solutions, such as Microsoft Copilot or Fabric data agents, is preferred.
Experience in operations, infrastructure, industrial, or another asset-intensive environment is preferred.

Responsibilities

Develop and maintain the Operations data-governance framework, roadmap, decision rights, and operating practices in alignment with enterprise standards.
Operationalize data-owner and data-steward responsibilities across Operations functions, including clear expectations, governance forums, escalation paths, and accountability.
Facilitate governance decisions and drive resolution of cross-functional data ownership, definition, quality, access, and usage issues.
Partner with business and data teams to identify critical data elements and establish quality rules, validation criteria, thresholds, and controls.
Monitor data-quality and trust indicators, identify root causes, and coordinate remediation with business owners, source-system owners, and data teams.
Maintain visibility into governance risks, ownership gaps, unresolved data issues, and remediation progress.
Establish and maintain Operations business definitions, metric definitions, ownership records, approved sources, and domain metadata.
Promote consistent use of governed definitions across data products, semantic models, dashboards, analytics, operational reporting, and AI-enabled solutions.
Coordinate documentation of data lineage and partner with Global Data & AI to align Operations practices with enterprise catalog, metadata, master-data, and reference-data standards.
Leverage approved AI-enabled, automation, and workflow tools to accelerate data discovery, metadata enrichment, definition development, issue triage, impact analysis, and steward support.
Partner with data engineering and platform teams to translate governance requirements into automated quality tests, controls, alerts, workflow triggers, and deployment checkpoints.
Evaluate emerging data- and AI-governance capabilities and recommend practical applications that improve governance effectiveness, adoption, and scalability.
Embed governance requirements and checkpoints into the lifecycle of data products, analytics, and AI solutions, from intake and design through deployment, change, and retirement.
Translate governance requirements into actionable acceptance criteria, documentation, controls, and remediation plans.
Operationalize enterprise AI-governance requirements within Operations by documenting intended use, data sources, and provenance; supporting risk assessment; and establishing appropriate quality, access, human-oversight, and monitoring controls.
Partner with business, data, technology, risk, and compliance teams to ensure solutions meet applicable requirements for security, privacy, transparency, and responsible use.
Develop practical playbooks, training, communications, and support resources for data owners, stewards, product teams, and data users.
Establish feedback loops across Operations, Operations Data & Intelligence, Global Data & AI, and technology teams to identify recurring gaps, drive cross-functional resolution, and incorporate lessons learned into governance practices.
Establish measures for ownership coverage, definition completeness, data quality, issue resolution, governance adoption, and maturity.
Continuously improve governance workflows and tools to increase transparency, accountability, usability, and scalability.
Analyze recurring data issues, user feedback, and governance metrics to identify root causes, emerging risks, and opportunities for automation and process improvement.