Revenue Operations Engineer

About the Role

We are looking for a technically sharp and strategically minded Revenue Operations Engineer who will own the full lifecycle of our Hub Spot ecosystem — from complex CRM migrations to the day‑to‑day architecture that powers our go‑to‑market engine. This is not a support role. You will be the primary point of contact for any Hub Spot‑related project: scoping, executing, communicating, and delivering.

You can zoom out to understand the business impact of a migration, and zoom in to fix a broken workflow or debug a data mapping at the field level.

• Lead end‑to‑end Hub Spot migrations: data mapping, object architecture, pipeline design, custom properties, and integrations with third‑party tools.
• Act as the sole technical POC for any migration project — from initial scoping calls with stakeholders to post‑migration QA and handover documentation.
• Design and implement Hub Spot workflows, sequences, lead scoring models, and attribution frameworks that reflect real business logic.
• Manage sandbox environments, version control on workflows, and rollback planning for high‑risk changes.
• Evaluate and integrate GTM tools (enrichment, routing, intent, enablement) into the Hub Spot ecosystem with clean data flows and minimal technical debt.

• Partner with Marketing, Sales, and Customer Success leadership to define the systems architecture behind each stage of the customer journey.
• Own the data model in Hub Spot — ensuring consistency, deduplication, and hygiene standards are upheld as the company scales.
• Proactively identify gaps between how teams operate and how systems are configured, and drive resolution before they become blockers.

• Serve as the named POC for every Hub Spot project — owning timelines, risk flags, stakeholder updates, and delivery accountability.
• Run discovery sessions with cross‑functional teams to gather requirements, surface edge cases, and document technical specs before any build begins.
• Produce clear project documentation: migration plans, field mapping logs, integration architecture diagrams, and post‑launch runbooks.
• Communicate fluently between technical collaborators (IT, developers) and non‑technical stakeholders (Sales leaders, CMOs) without losing precision in either direction.

• Build and maintain dashboards and reports in Hub Spot (and BI tools where needed) that give GTM leaders accurate, timely visibility into pipeline and revenue performance.
• Define and track the KPIs that matter for Rev Ops health: data quality scores, conversion rates by stage, tool adoption, and migration success metrics.
• Conduct post‑implementation reviews to validate that system changes produced the intended business outcomes.

• Use AI‑powered tools (e.g., Hub Spot AI features, Chat Spot, Breeze agents) to accelerate Rev Ops workflows — from automated data enrichment and lead scoring to AI‑assisted sequence writing and pipeline forecasting.
• Understand large language models (LLMs) to build, test, and iterate on prompts that improve internal documentation, workflow logic descriptions, and stakeholder reporting.
• Evaluate and integrate AI‑native GTM tools (e.g., Clay, Unify, 11x, Amplemarket) and assess their fit within the Hub Spot ecosystem — balancing automation gains against data quality and compliance requirements.
• Apply AI tools for data hygiene tasks: deduplication, normalization, and anomaly detection across CRM records at scale.
• Identify automation opportunities across manual Rev Ops processes and prototype AI‑assisted solutions using no‑code/low‑code AI platforms (e.g.,  with AI modules, Zapier AI, or custom GPT Actions).
• Stay current on AI developments relevant to Rev Ops — including agentic workflows, AI SDRs, predictive analytics tools — and proactively bring relevant capabilities to leadership’s attention.
• Ensure responsible AI usage within GTM systems: understanding data privacy implications, maintaining human oversight on AI‑driven decisions, and documenting AI‑assisted processes clearly.