Senior Data Analyst, GTM Analytics

Role: Senior Data Analyst, GTM Analytics

You will join Recharge’s central Data & Analytics team and support the Go-To-Market (GTM) organization, partnering with Sales, Business Development, Revenue Operations, and Demand Generation. The role blends analytics engineering, traditional analytics, and AI-first data product management to improve performance measurement and scale self-serve insights.

What you’ll do

• Analytics engineering (dbt + Looker):
  • Build and maintain durable, documented, tested datasets in dbt that power GTM reporting (pipeline, funnel, conversion, bookings, forecasting, rep performance, account health).
  • Create dimensional models (facts/dimensions), define metrics, and deliver “one version of the truth” datasets.
• Self-serve reporting (Looker):
  • Develop and maintain Looker explores, dashboards, and standardized reporting for GTM self-serve.
  • Implement data quality checks, monitoring, and model documentation.
• Collaboration with engineering & stakeholders:
  • Partner with data engineering on upstream improvements (instrumentation, source system hygiene, pipeline reliability).
  • Translate business questions into analysis plans, metrics, and decision frameworks with GTM stakeholders.
• Analysis & decision support:
  • Use SQL (and Python as needed) to analyze trends, diagnose performance issues, and recommend actions (funnel bottlenecks, win-rate drivers, deal velocity, territory/segment opportunities).
  • Build GTM narratives connecting data to decisions for leaders and cross-functional partners.
  • Monitor performance and adoption signals to surface risks, anomalies, and opportunities.
• Data products & AI/LLM acceleration:
  • Identify high-leverage GTM “insight bottlenecks” and design data products (e.g., KPI hubs, automated pipeline risk alerts, guided explorations, executive views).
  • Leverage LLMs/AI for:
    • AI-assisted metric explainers in dashboards
    • Natural-language Q&A over curated GTM datasets
    • Automated insight summaries/anomaly narratives
    • Guided self-serve templates for common GTM use cases
  • Define success metrics for data products (e.g., reduced time-to-insight, increased self-serve usage, fewer ad-hoc requests, improved forecast accuracy).
• Execution in ambiguity & communication:
  • Frame problems, generate hypotheses, and drive outcomes independently.
  • Manage multiple priorities and communicate via Slack, docs, and live stakeholder readouts.

Requirements

• Strong ability to build and maintain analytical models and reporting systems using dbt and Looker.
• Quantitative and business-minded analytics skills to deliver actionable insights.
• Ability to perform analysis using SQL; Python as needed.
• Strong stakeholder collaboration and ability to translate questions into analysis plans and metrics.
• Experience implementing data quality checks/monitoring and maintaining documentation.
• Ability to work in ambiguous environments and drive towards outcomes.
• Practical experience leveraging AI/LLMs to improve time-to-insight and self-serve adoption.

Nice-to-haves (implied)

• Experience defining dimensional models and metric taxonomies (“one version of the truth”).
• Experience building or maintaining data product workflows for self-serve insights (dashboards, KPI hubs, guided explorations, anomaly narratives).