Revenue Operations Analyst

Bizzabo, a leader in event technology, is looking for a strategic and highly analytical Revenue Operations Analyst in Ukraine to join our dynamic Revenue Operations Team. In this role, you will serve as a critical bridge between raw data and executive decision-making. You will be responsible for defining the analytical roadmap for our different GTM departments, ensuring that data is not just reported, but used as a competitive advantage to drive growth and efficiency.

We recognize that the best Revenue Operations talent often comes from diverse analytical paths. You are likely a strong match if you currently work in one of the following roles: Business Data Analyst: You are an expert at using complex SQL queries to uncover “The Why” behind the numbers, translating disparate datasets into analytical recommendations for leadership that will influence revenue decisions. Sales/Marketing Operations Analyst: You combine technical SQL mastery with deep CRM data knowledge to perform advanced analytics that optimize the B2B sales funnel and revenue predictability. Commercial BI Analyst: You are a SQL specialist who doesn’t just build “reports,” but architects sophisticated data models and dashboards to perform deep analytics on revenue and market trends.

Note on Fit: This is a Commercial Data & Strategy role. It is a great fit for those who love business strategy and deep analytics. It is not a fit for those focused on the SDLC, system analysis for software development, or writing technical requirements for engineering teams.

What You’ll Be Doing: Act as a dedicated strategic partner to GTM leadership (Sales, Marketing, and Customer Success) to provide the analytical support and insights needed to inform revenue decisions. Identify growth opportunities by analyzing CRM data to uncover actionable insights and resolve operational bottlenecks through end-to-end analytical project leadership. Encompass the full data lifecycle, from gathering requirements and deg complex data models with optimized SQL to architecting a scalable BI ecosystem in Looker that replaces manual reporting with sophisticated automation. Go beyond descriptive reporting and leverage modern AI-powered tools to accelerate your workflow. Uncover the underlying drivers of business performance and translate the data into clear narratives that inform decisions. Provide proactive insights and strategic recommendations based on key performance indicators. Continuously audit data quality and collection processes within the CRM to ensure a high-integrity, data-driven environment.

Required Experience & Skills Professional & Educational Background: 3+ years of experience as a Business/Data Analyst (preferably within a global SaaS or high-growth tech company) supported by a degree in Industrial Engineering, Statistics, Economics, or a related quantitative field. Technical Mastery: SQL Expert: Deep experience writing complex, optimized queries and working with modern data warehouses (e.g., Snowflake, BigQuery). BI Power User: Expert proficiency in Looker (LookML experience is a significant plus), Tableau, or similar enterprise BI tools. Data Manipulation: Advanced Excel skills for financial modeling and ad-hoc analysis. Business Acumen: Strong understanding of the SaaS business model and B2B sales funnels. Analytical Rigor: Proven ability to synthesize large, disparate datasets into clear, actionable business narratives. Communication: Fluent English with exceptional verbal and written communication skills. You must be able to explain technical concepts to non-technical business leaders. Cross-team collaboration: Strong communication skills and the ability to collaborate effectively with sales leaders and cross-functional teams Mindset: Highly independent, self-motivated, and excellent at multitasking to ensure management of multiple high-priority projects in a fast-paced environment while maintaining swift execution on daily tasks.

Preferred Qualifications Experience with AI-integrated analytics platforms or building automated workflows using AI agents. Familiarity with Salesforce, HubSpot and PlanHat data structures. Experience in fast-paced, SaaS, or startup environments.