Lead Data Analyst

About the Company

Cvent is a leading meetings, events, and hospitality technology provider with more than 5,000+ employees and 24,000+ 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.

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.

Disclaimer: Beware of Recruitment Scams – Legitimate Cvent recruiting communications will always come from an official [Confidential Information] 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

About the Role

The Analytics team is Cvent's internal intelligence engine — the function that powers how the business understands performance, serves commercial teams, and accelerates decision-making with data and AI. Within this organization, the data analytics function is responsible for turning raw data into governed, decision-ready insights that move teams from question to decision in minutes, not weeks. This role is designed for an experienced data analytics practitioner ready to step into a lead role within a scaling analytics organization. As Lead, Data Analytics, you will own day-to-day execution across data querying, transformation, dashboarding, and stakeholder-facing storytelling while remaining close to the work and raising the quality bar for the team.

The right person for this role brings strong business acumen alongside analytical depth. You can translate ambiguous business questions into well-structured analytical problems, write performant SQL against modern cloud warehouses, clean and validate messy data, partner with Data Science and Data Engineering on robust modeling, and turn findings into clear narratives that leadership and clients can act on.

What You Will Do:

Data Querying, Transformation, and Modeling

• Write and optimize complex SQL on Snowflake to query, join, aggregate, and reshape large datasets across multiple subject areas and source systems.
• Analyze and manipulate data to surface trends, anomalies, segments, and drivers that answer real business questions — not just produce numbers.
• Build clean, reusable data transformations and intermediate datasets that downstream dashboards, analyses, and stakeholders can rely on.
• Collaborate with Data Science on data modeling — preparing features, validating logic, and ensuring analytical datasets are well-structured for predictive and statistical workflows.
• Partner with Data Warehouse and Data Engineering teams to define requirements for new data sources, tables, and pipelines, ensuring analytics needs are reflected in upstream development.

Dashboarding and Storytelling

• Design, build, and maintain dashboards and visualizations that are accurate, intuitive, and tied to clearly defined business metrics.
• Translate analytical findings into compelling narratives — using storytelling techniques that connect data to business context, decisions, and outcomes.
• Create executive-ready presentations that distill complex analyses into a clear point of view, recommended actions, and supporting evidence.
• Present findings confidently to management, cross-functional partners, and clients, adapting depth and framing to the audience.
• Write easy-to-read reports and written summaries that stand on their own — readable without the analyst in the room.

Data Quality, Cleaning, and Validation

• Own data cleaning and normalization across analytical workflows — handling missing values, inconsistent formats, duplicates, and schema drift.
• Implement robust error handling and data validation checks to ensure outputs are accurate, reproducible, and trustworthy.
• Establish quality expectations for freshness, completeness, and accuracy in partnership with Data Engineering, and flag issues early.
• Document assumptions, transformations, and known limitations so that analyses are auditable and defensible.

Stakeholder Engagement and Business Impact

• Collaborate deeply with stakeholders across Product, Marketing, Sales, Customer Success, Finance, and Operations to understand priorities and shape the analytics roadmap.
• Apply strong business acumen to frame analyses in terms of revenue, retention, efficiency, and customer outcomes — not just metrics in isolation.
• Connect analytical insights to company strategy, helping leaders see how data should influence decisions on investment, prioritization, and go-to-market.
• Pitch data-driven solutions and recommendations to management and clients, building confidence through clarity, rigor, and well-supported reasoning.
• Act as a trusted analytics partner — proactive, responsive, and focused on moving stakeholders from question to decision.

What You Bring:

Experience

• 7 to 10 years in data analytics, business analytics, or a comparable role in enterprise software, B2B

SaaS, or data-driven environments.

• Demonstrated track record of owning end-to-end analytics work — from data extraction and

transformation through dashboarding, insight, and stakeholder delivery.

• Experience supporting multiple business functions and senior stakeholders

simultaneously, with a strong sense of prioritization.

Technical Depth:

• Strong SQL skills with hands-on experience querying databases in Snowflake (or comparable cloud data warehouses).

• Proficiency in analyzing and manipulating data — cleaning, normalizing, joining, and transforming datasets for downstream analysis.

• Experience collaborating with Data Science on data modeling, and with Data Warehouse

Data Engineering teams on requirements for new data development.

• Solid grounding in data validation, error handling, and quality checks across analytical pipelines and outputs.

• Proficiency with BI and dashboarding tools (e.g., Tableau, Looker, Power BI, Sigma, or similar) and

comfort building polished presentations.

• Python (or similar) for ad hoc analysis, automation, and notebook-based workflows is a plus.

Communication, Collaboration, and Business Acumen

• Strong storytelling and presentation skills — able to take a dense analysis and turn it into a clear,

persuasive narrative.

• Proven ability to write easy-to-read reports and structured written communication for executive and client audiences.

• Confident presenter who can hold the room with leadership, cross-functional partners, and external clients.

• Sharp business acumen — understands how analytical insights can drive company strategy,

commercial outcomes, and operational decisions.

• Strong stakeholder collaboration and engagement skills, with a bias toward partnership, clarity, and trust-building.

• Track record of pitching data-driven solutions and seeing them adopted by management and clients.