Sona is the next-generation workforce management solution for large frontline operators, where consumer grade design is matched by AI-driven decision making.

Combining end-to-end WFM functionality - including Scheduling, Time & Attendance, HR and Payroll - with truly intelligent AI capabilities, Sona enables real-time actionable insights geared towards driving revenue and increasing employee satisfaction.

About the Role

The Revenue Operations - Systems & Data role at Sona will own the integrity, architecture, and administration of our go-to-market data foundation. This is the role that makes sure our revenue engine runs on clean, trustworthy, well-structured data, and that every system in our GTM stack talks to every other system reliably.

You'll be responsible for how data flows across HubSpot, Gong, Lemlist, LinkedIn Sales Navigator, and the wider GTM stack: designing schemas, enforcing hygiene standards, building integrations, and ensuring our CRM is the single source of truth for the commercial team. As Sona scales its AI capabilities across the revenue function, the quality of that foundation becomes critical. AI is only as good as the data it sits on, and this role ensures ours is solid.

This role sits within Revenue Operations, and works closely with Sales, Marketing + wider GTM org. It's a hands-on, technically deep role for someone who gets genuine satisfaction from well-structured data, clean integrations, and systems that just work.

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

Technical skills

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

GTM & business understanding

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