Coralogix is building a next-generation Revenue Operations function, and this role sits at its analytical center. You’ll turn data into decisions—partnering closely with Sales and RevOps leadership to improve pipeline health, forecast accuracy, territory coverage, and go-to-market performance.

This is an analytics role (not a reporting-only or systems-admin role). Success is measured by the quality of insights you deliver and the actions those insights unlock.

What you’ll do

• Partner with US Sales leadership in deal reviews, forecast calls, and QBRs—bringing clear, executive-ready insights and recommendations.
• Diagnose pipeline health, identify deal-pattern anomalies, and surface rep productivity signals to drive coaching and operating rhythm improvements.
• Lead quota modeling, target-setting, territory coverage analysis, and capacity planning for annual and mid-year planning cycles.
• Build and maintain ICP scoring, account tiering, and enrichment-driven segmentation using Enrichment tools and internal frameworks.
• Analyze churn patterns, win/loss trends, and deal velocity to inform decisions across Sales, Finance, and Customer Success.

Own analytical products (not one-off reporting)

• Co-own the analytical layer of core GTM products with GTM Engineering, including forecast intelligence, pipeline health dashboards, deal scoring, and territory performance models.
• Define requirements, validate inputs, and own the business logic and insight layer. (Engineering owns the infrastructure; you own the analytical conclusions.)
• Build strategic, versioned dashboards and analytical deliverables for GTM leadership.
• Query and validate the Snowflake data layer as the source of truth.

Data quality & governance

• Help ensure accuracy of GTM data across Salesforce and integrated tools by auditing, resolving discrepancies, and reinforcing governance standards.
• Document reporting definitions, segmentation logic, and data standards so teams operate from a shared source of truth.

Operational support (as needed)

• Provide deal desk support during team build-out (e.g., deal structuring, quoting support, approval workflows, closed-lost reviews).

AI-native ways of working

• Use LLMs (Claude, GPT, etc.) as a core part of daily work—synthesizing call data, accelerating analysis, structuring territory reviews, and drafting executive-ready narratives.
• Identify repetitive manual workflows and build or propose AI-assisted solutions to eliminate them.
• Stay current on automation tooling (e.g., n8n, Clay, Apollo) and recommend improvements proactively.