The Staff Analyst, GTM Analytics partners with Marketing leadership to improve pipeline generation, conversion, campaign ROI, and data governance. The role requires 7+ years in analytics or BI, advanced SQL, dbt, Python, and experience with B2B marketing technology and AI-driven analytics workflows.
163k – 214k/yr
Hybrid7+ YOEData Analytics
About the role
Responsibilities
Partner with Marketing executives to align analytics initiatives with global business objectives, technical roadmaps, and investment decisions.
Surface insights that influence pipeline generation, conversion optimization, and campaign ROI.
Maintain data models, metrics, and pipelines supporting GTM reporting using SQL, dbt, and Snowflake.
Partner with Analytics Engineering and Data Engineering teams to build, debug, and extend models.
Transform workflows through AI systems and architect secure solutions that improve internal and stakeholder efficiency.
Ensure data integrity across Salesforce, Marketo, and Snowflake through automated testing and reconciliation.
Lead data infrastructure improvements and scalable governance practices.
Represent the company in the business intelligence space, champion analytics innovation, and engage with customers to share best practices.
Requirements
7+ years of experience in Analytics or Business Intelligence within large-cap technology companies or high-growth SaaS environments.
Advanced SQL, hands-on dbt proficiency, and strong Python skills for data transformation, analysis, and AI-powered data applications.
Experience partnering directly with Marketing leadership to drive strategic decisions.
Understanding of pipeline generation, conversion rates, and campaign ROI.
Experience with or strong interest in AI-driven analytics workflows, including semantic models, text-to-SQL, Cortex Analyst, or similar natural-language data interfaces.
Experience using Python and data application frameworks such as Streamlit.
Proven experience with B2B marketing technology stacks, including Salesforce and Marketo, Eloqua, or HubSpot.
Familiarity with Airflow, dbt, Snowflake, and related data pipeline ecosystems.
Ability to present to, advise, and challenge VP-level stakeholders across cultures and time zones.
Work Arrangement
Hybrid role requiring three days in the office in Menlo Park.
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