Revenue Operations Analyst

Responsibilities Maintain and administer Sona's GTM data model day to day: properties, objects, associations and lifecycle stages across HubSpot and connected systems, under the direction of the Head of RevOps Build and maintain integrations between GTM platforms (HubSpot, Gong, Lemlist, Sales Navigator, Cognism, Planhat, and others), ensuring data flows reliably and bi-directionally where needed Enforce data quality standards across the CRM: deduplication, enrichment, validation rules, and ongoing hygiene programmes to keep our contact, company, and deal data trustworthy Design and maintain reporting infrastructure: dashboards, custom reports, and data views that give revenue leaders accurate, timely visibility into pipeline, conversion, and attribution Build and manage workflow automations in HubSpot and n8n that reduce manual work for the commercial team while maintaining data integrity Support the development of a reliable data foundation that AI tools and agents can build on, working closely with the Growth AI Engineer to ensure systems are structured for programmatic access Document system architecture, data dictionaries, integration maps, and operational standards so the team can scale without tribal knowledge Troubleshoot and resolve system issues, integration failures, and data discrepancies quickly and methodically Evaluate and onboard new GTM tools as needs evolve, managing vendor relationships and technical implementation Qualifications At least 2-4 years of hands‑on experience administering and configuring CRM platforms, ideally HubSpot Strong understanding of data architecture principles: schema design, object modelling, data normalisation, and relational data structures Experience building and maintaining system integrations using APIs, middleware (e.g. n8n, Zapier, Make), or native connectors Comfortable writing or debugging simple scripts to manipulate or transform data (Python, JavaScript or similar) is a plus Experience with data quality tooling and practices: deduplication, enrichment, validation, and hygiene automation Familiarity with reporting and analytics tools: building dashboards and custom reports that revenue teams actually trust and use Active, fluent use of AI tools in your own work, and a clear understanding of why clean, structured data underpins AI effectiveness Solid understanding of B2B SaaS sales cycles, marketing funnels, and how data supports revenue operations Hands‑on experience with GTM platforms beyond CRM (e.g. Gong, Lemlist, Sales Navigator, Cognism, ZoomInfo, Clay, Planhat) Ability to diagnose complex data and system issues end‑to‑end: from root cause to resolution Comfortable working in evolving, imperfect systems and improving them methodically over time Able to clearly explain data and systems concepts to non‑technical stakeholders Comfortable working cross‑functionally with Sales, Marketing, CS, and Product teams #J-18808-Ljbffr