UTM.io
Website:
utm.io
Job details:
Cvent is a leading meetings, events, and hospitality technology provider with more than 5,500+ employees and 30,000+ customers worldwide, including 60% of the Fortune 500. Founded in 1999, Cvent delivers a comprehensive event marketing and management platform for marketers and event professionals and offers software solutions to hotels, special event venues and destinations to help them grow their group/MICE and corporate travel business. Our technology brings millions of people together at events around the world. In short, we’re transforming the meetings and events industry through innovative technology that powers the human connection.
Cvent's strength lies in its people, fostering a culture where everyone is encouraged to think like entrepreneurs, taking risks and making decisions confidently. We value diverse perspectives and celebrate differences, working together with colleagues and clients to build strong connections.
Disclaimer: Beware of Recruitment Scams – Legitimate Cvent recruiting communications will always come from an official ‘name@cvent.com’ email. We never request any payments or ask for sensitive personal or financial information via chat or social media platforms. For more information, please visit: https://www.cvent.com/en/notice-recruitment-fraud
AI at Cvent: Leading the Future:
Are you ready to shape the future of work at the intersection of human expertise and AI innovation? At Cvent, we’re committed to continuous learning and adaptation—AI isn’t just a tool for us, it’s part of our DNA. We’re looking for candidates who are eager to evolve alongside technology. If you love to experiment boldly, share your discoveries, and help define best practices for AI-augmented work, you’ll thrive here. Our team values professionals who thoughtfully integrate AI into their daily work, delivering exceptional results while relying on the human judgment and creativity that drive real innovation.
Throughout our interview process, you’ll have the chance to demonstrate how you use AI to learn, iterate, and amplify your impact. If you’re excited to be part of a team that’s leading the way in AI-powered collaboration, we’d love to meet you.
Position Description:
As a Digital Data Governance Analyst, you will own the structure, quality, and consistency of how Cvent's internal knowledge and data is classified, labeled, and maintained. That means managing our business glossary, governing the metadata layer that our AI tools depend on, and building the standards and workflows that keep information accurate as the organization scales.
This is not a compliance role — it is an infrastructure role. The taxonomy and governance systems you maintain are what allow our AI tools to return accurate, trustworthy answers. Without active stewardship, those tools degrade silently. With it, they compound in value.
You will work across Engineering, Product, Finance, and Operations, serving as the cross-functional authority on how data concepts are defined and classified. You will use AI heavily to scale your output — applying schemas, scanning for ungoverned content, and drafting definitions — but the judgment, resolution, and governance is yours.
What you will be doing:
- Own and maintain Cvent's enterprise data glossary, ensuring term definitions are accurate, current, and consistent across teams
- - Apply and enforce classification schemas across databases and knowledge bases
- - Drive cross-team alignment on shared business concepts (e.g., "customer," "event," "account") to prevent divergent definitions across reports and systems
- **Data Catalog Stewardship**
- - Govern the unified metadata graph across 130+ connected data sources
- - Maintain business ontologies and keep the semantic context layer accurate as systems and processes change
- - Monitor and remediate drift in data tiering, certification, and lineage tracking
- - Partner with Engineering to ensure new pipelines are cataloged at launch, not after the fact
- **Content & Knowledge Operations**
- Manage the label taxonomy for the enterprise wiki, enabling consistent content classification and discoverability
- Lead the org-wide rollout of the master label system (framework already built — execution is the priority)
- Own content lifecycle governance: enforce sunsetting and auto-archive workflows to keep the knowledge base clean and AI-ready
- Apply structured metadata to OKRs, documentation, and knowledge base entries to improve retrieval quality
- **AI-Augmented Operations**
- Use AI tools to scale classification, surface ungoverned content, and draft glossary definitions
- Set the schemas and governance rules that AI agents operate within
- Review AI-generated outputs for edge cases and business context that automation cannot resolve
- **Standards & Enablement**
- Establish and document data classification standards that other teams can apply independently
- Build governance processes that are sustainable — not dependent on tribal knowledge
- Serve as the internal expert on data quality and classification best practices
What you will need for this position:
Required Qualifications:
- 2–4 years of experience in data governance, information architecture, knowledge management, or a related field
- Demonstrated experience managing data glossaries, metadata schemas, or classification taxonomies in an enterprise environment
- Familiarity with data catalog platforms (Collate, OpenMetadata, Alation, Atlan, or similar)
- Strong cross-functional communication skills — you will regularly mediate term definitions between teams with competing perspectives
- Comfort working with AI tools as a force multiplier, not a replacement for judgment
Preferred Qualifications:
- Hands-on experience with Collate or OpenMetadata specifically
- Experience with Snowflake or other cloud data warehouse environments
- Familiarity with enterprise wiki platforms (Confluence or similar) and content governance workflows
- Exposure to enterprise search tools (Glean or similar) and how content classification affects retrieval quality
- Experience building governance processes from scratch or formalizing informal systems
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