Sr. Data Analyst

Responsibilities:

• Develop and maintain reports and dashboards that track core Sales and PLG KPIs, including trial conversion, product adoption, feature activation, and revenue performance.
• Serve as the Operational Intelligence team's analytics partner for Sales and Revenue Operations, translating business questions into reliable, actionable reporting.
• Build and maintain data models in Snowflake that support sales and PLG analytics use cases for the Pave product.
• Contribute to our centrally governed data layer by authoring and submitting dbt pull requests that extend our enterprise data models for GTM use cases.
• Collaborate closely with data engineering to align on modeling standards, data quality practices, and pipeline dependencies.
• Partner with Revenue Operations to ensure GTM metrics, including free trial signups, time-to-activate, product-qualified leads, trial conversion, and expansion signals, are consistently defined and trusted across reporting.
• Support operating mechanisms including GTM business reviews, reporting cadences, and recurring operational processes where data accuracy and timeliness are critical.
• Identify trends in product usage and PLG motion that inform sales strategy and prioritization.
• Enable self-service analytics by building reusable datasets and maintaining clear, accessible documentation.
• Ensure data quality and consistency across sales and product analytics workflows.

Requirements:

• 5 to 8 years of experience in data analytics, business intelligence, or GTM/sales analytics roles.
• Strong SQL skills with solid experience in data modeling and working with cloud data platforms, ideally Snowflake.
• Demonstrated experience supporting Sales, Revenue Operations, or GTM teams in a SaaS environment, including supporting business reviews and recurring reporting cadences.
• Strong understanding of how operational teams consume and act on data, not just how to model it.
• Solid understanding of PLG concepts, product usage analytics, and GTM metrics.
• Hands-on experience contributing to dbt projects, including writing models, tests, and documentation.
• Ability to define and standardize business metrics across stakeholder groups.
• Strong communication skills, able to present data clearly to both technical and non-technical audiences.
• Comfortable working cross-functionally in a globally distributed, async-friendly environment with some US business hours overlap.

Nice to Have:

• Experience with Power BI or comparable BI and data visualization tools.
• Experience with CRM data (Salesforce) and revenue analytics platforms.
• Familiarity with PLG tools or product analytics platforms such as Amplitude, Mixpanel, or Pendo.
• Exposure to data governance and data quality frameworks.
• Experience working in a product-led or hybrid sales-led/PLG SaaS organization.

What Success Looks Like:

• Sales and Revenue Operations teams have reliable, consistent visibility into trial conversion, PLG signals, and expansion opportunities.
• PLG signals from Pave are systematically tracked and surfaced to inform sales prioritization.
• Key GTM metrics are clearly defined, documented, and trusted across the organization.
• Operating mechanisms, including GTM business reviews and reporting cadences, are consistently supported with accurate, timely data.
• Self-service reporting adoption grows within Sales and Revenue Operations teams.
• Contributions to the central DBT model are well-tested, documented, and aligned with enterprise standards.
• Strong working relationships are established with Data Engineering and Revenue Operations counterparts.