Responsibilities

• Be a Strategic Partner to Leadership: Partner with Marketing executives to align analytics initiatives with global business objectives — active GTM alignment, technical roadmap strategy, shaping investment decisions, and proactively surfacing insights that move the business, not just inform it.
• Turn Data into Business Outcomes: Go beyond reporting to influence pipeline generation, conversion optimization, and campaign ROI — presenting complex analytical findings to the team with clarity and impact. You measure success by decisions changed, not dashboards shipped.
• Master the Analytical Foundation: Maintain deep fluency in the data models, metrics, and pipelines (SQL, dbt, Snowflake) that power GTM reporting. Partner closely with Analytics Engineering and Data Engineering teams to ensure insights are accurately surfaced — and step in hands-on-keys when needed to build, debug, or extend models.
• Amplify Reach with AI & Automation: Automating trivial workflows is just the surface - transform the way we work through AI systems and architecting secure solutions for both internal and stakeholder efficiency.
• Champion Data Quality & Governance: Ensure data integrity across source systems (Salesforce, Marketo, Snowflake) through automated testing and reconciliation. Spearhead data infrastructure improvements and best practices the team can trust at scale.
• Establish Thought Leadership: Represent the company in the business intelligence space at industry events and champion innovation across the analytics org. Engage with customers regularly to share best practices and evangelize our work.

Requirements

• Technical Mastery: 7+ years of experience in Analytics/BI within large-cap tech companies or high-growth SaaS environments; featuring advanced SQL, hands-on dbt proficiency, and strong Python skills for data transformation, analysis, and building AI-powered data applications.
• Business Acumen & Strategic Partnership: A track record of partnering directly with Marketing leadership to drive strategic decisions. You think in terms of pipeline, conversion rates, and campaign ROI — not just tables and joins.
• AI & Innovation Literacy: Experience with or strong interest in building AI-driven analytics workflows — including semantic models, text-to-SQL, Cortex Analyst, or similar natural-language data interfaces — using Python and data app frameworks like Streamlit.
• Marketing Domain Expertise: Proven experience with B2B marketing technology stacks (Salesforce, Marketo/Eloqua/HubSpot) and familiarity with the data pipeline ecosystem (Airflow, dbt, Snowflake).
• Executive Presence: Comfortable presenting to, advising, and pushing back on VP+ stakeholders — with the ability to work across different cultures and time zones.