Senior Data Analyst, GTM Analytics

Who we are

Recharge is the subscription platform for the world’s fastest-growing and most innovative brands. Shopify’s premier subscription solution, Recharge is on a mission to build the future of commerce around customer retention.

Known for its relentless product innovation and focus on ease of use, Recharge helps merchants deliver seamless customer experiences that drive customer retention and revenue growth. The Recharge platform leverages data from over 100 million shoppers to help brands more successfully set up, manage, and grow their subscription businesses.

Recharge is a hands‑on partner to over 20,000 brands globally — including quip, Dr. Squatch, Blueland, Estrid, Oats Overnight, Bobbie, and more.

Learn more at:

We’re hiring a Senior Data Analyst to support our Go‑To‑Market Organization (Sales, Business Development, Revenue Operations and Demand Generation). You will report into our central Data & Analytics team and partner closely with GTM leadership to improve how we measure performance, identify growth opportunities, and scale self‑serve insights across the organization.

This role blends:

• Analytics Engineering
  : building trusted, well‑modeled data sets in dbt and scalable reporting in Looker
• Traditional Analytics
  : applying business acumen, curiosity, and strong quantitative skills to deliver impactful insights
• Data Product Management (AI‑first): leveraging LLMs/AI to design and ship data products that meaningfully improve time‑to‑insight and self‑serve adoption

• Live by and champion all of our core values #accountability, #collaboration, #iteration, and #details
• Build and maintain durable, documented, tested models in dbt that power GTM reporting (e.g., pipeline, funnel, conversion, bookings, forecasting, rep performance, account health).
• Design dimensional models (facts/dimensions), metrics definitions, and “one version of the truth” datasets to make analysis repeatable and trustworthy.
• Develop and maintain Looker explores, dashboards, and standardized reporting that enable self‑serve by the GTM organization.
• Implement data quality checks, monitoring, and model documentation so stakeholders can confidently act on results.
• Partner with data engineering on upstream improvements (instrumentation, source system hygiene, pipeline reliability).
• Collaborate with GTM stakeholders to clarify business questions and translate them into analysis plans, metrics, and decision frameworks.
• Perform analysis using SQL (and Python as needed) to identify trends, diagnose performance, and recommend actions (e.g., funnel bottlenecks, win‑rate drivers, deal velocity, territory/segment opportunities).
• Build GTM narratives that connect data to decisions—clearly communicating insights with business context to leaders and cross‑functional partners.
• Proactively monitor performance and adoption signals to surface risks, anomalies, and opportunities—then drive stakeholders toward resolution.
• Identify high‑leverage GTM “insight bottlenecks” and design data products to solve them (e.g., standardized KPI hubs, automated pipeline risk alerts, self‑serve funnels, guided explorations, executive views).
• Leverage LLMs/AI to accelerate insight workflows—examples might include:
  • AI‑assisted “metric explainers” embedded into dashboards
  • Natural‑language Q&A experiences over curated GTM datasets
  • Automated insight summaries / anomaly narratives for weekly GTM reviews
  • Guided self‑serve templates (“answer this question in 3 clicks”) for common GTM use cases
• Establish success metrics for data products (e.g., reduced time‑to‑insight, increased self‑serve usage, fewer ad‑hoc requests, improved forecast accuracy).
• Work independently in ambiguous environments—framing problems, generating hypotheses, and leading toward outcomes.
• Manage multiple priorities and communicate clearly through Slack, docs, and live stakeholder readouts.
• Contribute to team standards (modeling patterns, documentation, code review, stakeholder intake).
• Mentor other analysts through collaboration, query/design feedback, and best practices (where applicable to your team structure).

• 5+ years of experience using analytics to solve business problems…