Revenue Ops Architect: Own Data & Territory

7AI

Boston (MA)

On-site

USD 90,000 - 130,000

Full time

3 days ago
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Job summary

7AI in Boston is seeking a Revenue Operations professional to own the end-to-end go-to-market data, from Salesforce as system of record to territory design. You will build processes in-flight, automate recurring data tasks, and provide dashboards that leadership relies on to steer pipeline and quota performance.

The role emphasizes hands-on Salesforce, data hygiene, and AI-enabled tooling, with a bias toward shipping iteratively even if inputs aren’t perfect.

Qualifications

  • 2+ years in revenue operations, sales operations, or business analytics.
  • Bachelor's degree in a quantitative or analytical field or equivalent practical experience.
  • Experience at a startup or high-growth company.
  • Hands-on Salesforce experience, including reports, dashboards, data model, and flows.

Responsibilities

  • Territory design, including segmentation and model maintenance to balance coverage and capacity.
  • Salesforce data integrity: de-dup, enrichment, firmographic accuracy, ownership rules, and validation logic.
  • Reporting and analyses for leadership: pipeline coverage, stage conversion by segment, rep productivity, territory performance.
  • Automating recurring data tasks and reporting workflows.
  • Quotas and compensation support, forecast cadence, tooling evaluations.

Skills

Excel / Sheets proficiency
Strong communication
AI tooling fluency
Bias toward iterative shipping

Education

Bachelor's degree in quantitative/analytical field or equivalent

Tools

Salesforce

Job description

7AI in Boston is seeking a Revenue Operations professional to own the end-to-end go-to-market data, from Salesforce as system of record to territory design. You will build processes in-flight, automate recurring data tasks, and provide dashboards that leadership relies on to steer pipeline and quota performance.

The role emphasizes hands-on Salesforce, data hygiene, and AI-enabled tooling, with a bias toward shipping iteratively even if inputs aren’t perfect.

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