AI Analytics Engineer (Marketing Analytics)

Airtable•Austin, TX

13h

About The Position

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.

Requirements

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.
Full-stack Mindset: You own problems end-to-end and drive the solution, even if it requires expanding the original scope.
Bias for Action: You prioritize effective delivery over perfection, operating with a 'ship, learn, and iterate' mentality.
Genuinely AI-Native: AI tools are fundamental to your work process. You leverage them to write cleaner SQL, debug models faster, generate documentation, and prototype solutions, and can articulate your specific usage.
Data Storyteller: You provide definitive business closure—framing findings as actionable recommendations, not just delivering technically correct output.
Thrives in Ambiguity: You proactively create clarity and forward momentum, even when requirements are incomplete or rapidly changing.

Nice To Haves

Python for data work (pandas, ETL scripting, or analysis).
Prior exposure to marketing data concepts: attribution, funnel metrics, lead scoring, or campaign performance.
Familiarity with CRM (Salesforce) or marketing automation platforms (Marketo).
Experience with Databricks or cloud data warehouses.
A public portfolio showcasing data or AI-assisted engineering work (GitHub, personal projects, Kaggle).

Responsibilities

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 data insights into clear business recommendations via dashboards, memos, and presentations.
Domain Expertise
Achieve a comprehensive mastery of Airtable's marketing data models, existing pipelines, and BI tools (dbt / Looker / Omni) within the first 6 months, becoming the definitive internal expert.