Senior Data Analyst
Location: Canada Remote
We are seeking a Data Analyst to lead the most critical analyses and measurement frameworks across the GTM business. This will be a high-impact individual contributor role for someone who can own ambiguous problem spaces, build trusted executive-level insights, and raise the bar for analytics rigor, metric consistency, and storytelling.
This role will partner with senior stakeholders across GTM (Sales/RevOps/CS), Product, and Finance to define success metrics, perform source system discovery, build scalable data solutions, reporting and insight engines, and drive measurable outcomes. This role will work closely with Data Engineering and Analytics Engineering, is highly hands-on in analysis (SQL), source system discovery, functional and technical requirements, UI design, enablement, and insight delivery.
Key Responsibilities
- Lead High-Stakes, Ambiguous Analytics (Hands-On)
- Own end-to-end analytics for strategic initiatives (e.g., growth, retention, renewals, pipeline health, product adoption, customer outcomes).
Translate ambiguous business questions into crisp analytical plans: hypothesis data needs method results- action.
Deliver executive-ready insights with clear recommendations, tradeoffs, and measurable impact.
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Define Metrics, Measurement, and Decision Systems
- Establish and enforce consistent definitions for core KPIs (ARR/NRR, churn, pipeline coverage, expansion, activation, retention, usage).
- Design measurement approaches for complex motions (multi-touch attribution, cohort retention, funnel conversion, renewals risk).
Build scalable scorecards and operating cadences (weekly business review, monthly ops review, QBR packs).
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Build Scalable Analytics Assets (Not Just One-Offs)
- Partner with Analytics Engineering / Data Architecture to translate logic into durable datasets, marts, and semantic definitions.
- Create reusable analytical frameworks:
- cohort and segmentation models
- driver trees and decomposition
- leading indicator dashboards and alerting definitions
Ensure analysis is repeatable, versioned, and production-minded.
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Advanced Analytics & Causal Thinking
- Experience with Diagnose drivers and root causes (variance analysis, decomposition, pathway analysis, survival/retention patterns).
Exposure to building pragmatic forecasting/what-if models (pipeline scenarios, renewal outcomes, capacity planning).
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Executive Storytelling & Stakeholder Leadership
- Act as a thought partner to leaders: shape decisions, not just report numbers.
- Develop crisp narratives that connect metrics to actions: “what happened, why, what to do next.”
- Raise analytics standards through mentorship, templates, review processes, and best practices.
- Shape
