AI Analytics Engineer (Marketing Analytics)
Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done.
What this role actually needs.
AI Analytics Engineer (Marketing Analytics) at Airtable in Austin. UpJobz keeps this listing high-signal for applicants targeting serious high-tech roles across the United States, Canada, and Mexico. Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done.
Day-to-day expectations
A clear list of the work this role is designed to cover.
- Canonical Marketing Data Sources Design and maintain trustworthy data models for core marketing metrics, managing the full lifecycle from prototyping through production.
- Develop and govern dbt data pipelines, establishing data integrity standards and SLAs for timely, accurate delivery across the Marketing organization.
- Critical Dashboards and Self-Serve Tooling Build and optimize dashboards that deliver real-time, self-serve insights across high-priority marketing areas: campaign performance, funnel conversion, pipeline contribution, and lead scoring.
- Drive data independence for Marketing stakeholders, eliminating reliance on ad-hoc data requests and manual reporting.
- AI-Native Data Infrastructure Collaborate with the Marketing team and data partners to establish the AI Business Context layer for marketing use cases.
- Lead the development of tools that facilitate natural language data access and AI-assisted reporting for non-technical stakeholders.
What a strong candidate brings
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- Must-Have Expert-level SQL: Proven ability to write complex queries involving joins, aggregations, and window functions.
- Proficiency with dbt or equivalent data transformation tools.
- Experience with BI and visualization platforms (Looker, Omni, Tableau, Hex, or similar).
- Active, demonstrated daily use of AI coding tools (Cursor, Claude, ChatGPT, Gemini). Candidates must provide specific, concrete examples of how these tools are integral to their work, moving beyond simple familiarity.
- Mandatory use of GitHub for version control in a standard development workflow.
- Exceptional communication skills: the ability to translate technical data findings into compelling business narratives for non-technical leadership.
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