AI Analytics Engineer (Marketing Analytics)

Job Description

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. Airtable’s Data Science & Analytics team seeks an Analytics Engineer to embed within our Marketing organization. This is a high-impact, early-career role. You will be responsible for building the canonical data infrastructure, owning critical dashboards, and enabling Marketing stakeholders to execute faster, more confident, data-driven decisions. We require a genuinely AI-native professional—not merely familiar with tools like Claude, Cursor, or ChatGPT, but one who integrates them as a core part of their daily workflow. The successful candidate will possess a full-stack mindset, a bias for action, and deep curiosity about how marketing data drives tangible business outcomes. About the Team The Data Science & Analytics team at Airtable is the company-wide partner for building data infrastructure, metrics, and insights that directly inform decision-making. The Marketing Analytics Engineer will embed with the Marketing organization, working directly with GTM data and Airtable's core data stack: dbt, Databricks, Looker, and Omni. Note on Leveling : We’re particularly interested in candidates with 1–4 years of professional experience. What you'll do 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. Trusted Partnership Serve as the primary data partner for marketing managers, demand generation teams, and leadership. Translate complex

Required Skills