Live by and champion all of our core values (#ownership, #empathy, #day-one, and #humility).
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).

Requirements

5+ years of experience using analytics to solve business problems in fast-paced environments.
Advanced SQL skills and a track record of delivering actionable insights to non-technical stakeholders.
Strong experience in analytics engineering:
dbt (dimensional modeling, testing, documentation, version control workflows)
Looker (explores/dashboards, scalable self-serve design)
Experience translating ambiguous business questions into metrics, analyses, and recommendations—then driving alignment with GTM leaders.
Strong communication skills across audiences (GTM leadership, RevOps, Finance, Product, Engineering).
High self-sufficiency, strong judgment, and comfort making tradeoffs under time constraints.
Demonstrated experience leveraging LLMs/AI to improve business workflows (or strong evidence you can ramp quickly and apply AI pragmatically).
Product mindset: you think in terms of users, adoption, impact, and measurable outcomes—not just outputs (queries/dashboards).
Experience supporting GTM analytics (pipeline, forecasting, productivity, territories, win-rate, funnel conversion).
Experience in Snowflake and modern analytics stack operations.
Nice to have Python proficiency for deeper analysis, automation, or prototyping.
Payments and/or ecommerce experience.

Benefits

Medical, dental and vision plans
Retirement plan with employer contribution
Flexible Time Off
Paid Parental Leave
Monthly Remote Life and Merchant stipends

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLdbtLookerdimensional modelinganalytics engineeringdata quality checksdata documentationLLMsPythonanalytics

Soft Skills

communicationproblem framinghypothesis generationindependencejudgmenttradeoff decision-makingmentoringcollaborationself-sufficiencyclarifying business questions