Senior Data Analyst, GTM Analytics
Accountabilities Deliver decision-ready analysis across Sales, Marketing, and Client Success, covering pipeline health, funnel conversion, campaign and channel performance, cohorts, retention, and GRR/NRR drivers.
Partner directly with business stakeholders to define analytical questions, develop recommendations, and carry insights through to business decisions rather than simply delivering reports.
Translate ambiguous stakeholder requests into structured, testable analytical approaches with clear objectives and measurable outcomes.
Build and maintain dbt models and data marts supporting Sales, Marketing, and Customer Success, using Salesforce as a core source system.
Own data quality and documentation for assigned domains, establishing reliable definitions, source-of-truth datasets, and quality assurance practices.
Contribute to the development of a BI-as-code environment, helping define how dashboards, metrics, and semantic models are created, versioned, reviewed, and maintained.
Help advance agentic analytics workflows by using AI agents to accelerate analysis, automate recurring reporting, and reduce manual dashboard requests.
Evaluate where AI can effectively replace or augment manual analytical work while maintaining appropriate human oversight and analytical rigor.
Use Python, SQL, dbt, and AI-assisted development tools to automate repetitive tasks and improve analytical efficiency.
Manage an individual analytics backlog within two-week sprints, aligning priorities with team objectives and communicating progress proactively.
Collaborate closely with Analytics Engineering and GTM leadership to ensure analytical solutions are scalable, accurate, and directly connected to business priorities.
Requirements
5+ years of experience in analytics or business intelligence, including meaningful experience supporting Sales, Marketing, or Customer Success within a fast-growing organization.
Demonstrated ability to own complex or ambiguous analytical problems end-to-end and provide strategic direction beyond routine reporting.
Expert-level SQL skills and hands-on experience building and maintaining dbt models for go-to-market data.
Strong experience working with Salesforce data, including familiarity with CRM objects, fields, relationships, and common data-modeling challenges.
Comfortable using Python for analysis, automation, and eliminating repetitive manual workflows.
Experience with modern data stacks, including tools such as Fivetran or comparable EL platforms and cloud data warehouses such as Snowflake or BigQuery.
Familiarity with modern BI platforms such as Sigma, Hex, Tableau, Looker, or comparable tools is highly desirable.
Understanding of governed semantic layers, self-service analytics, BI-as-code, and modern data organization practices.
Genuine interest in agentic analytics and hands-on experience using AI agents or LLM-based tools to accelerate analytical work.
Experience with Claude Code, Codex, or similar coding agents is a strong advantage.
Strong communication skills, with the ability to explain analytical findings and recommendations clearly to non-technical stakeholders and confidently defend conclusions.
Strong ownership and follow-through, taking responsibility for deliverables from initial question through final outcome.
Comfortable operating in ambiguous, rapidly changing environments and delivering iteratively through short development cycles.
Benefits
Competitive salary: $145,000–$175,000 per year.
Remote work: Fully remote position based in the United States.
High-impact analytics: Direct influence over Sales, Marketing, and Client Success strategy and decision-making.
Modern data environment: Opportunity to work with SQL, dbt, Salesforce, cloud data infrastructure, BI-as-code, and modern analytics practices.
AI-forward culture: Hands-on opportunity to help develop agentic analytics workflows and integrate AI into everyday analytical processes.
Cross-functional collaboration: Close partnership with business leaders and analytics engineering teams.
Fast-paced delivery: Work within two-week sprints where analytical projects move quickly from concept to implementation.
Professional growth: Opportunity to shape an evolving analytics function and establish scalable standards for GTM data and decision support.
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