# AI Analytics Engineer (Marketing Analytics)

**Company**: Airtable
**Location**: San Francisco, CA; Austin, TX; New York, NY
**Work arrangement**: remote
**Experience**: entry
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/airtable/jobs/8434307002
**Canonical**: https://yubhub.co/jobs/job_df625390-342

## Description

We're seeking an AI Analytics Engineer to join our Data Science & Analytics team. As 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.

You will design and maintain trustworthy data models for core marketing metrics, manage the full lifecycle from prototyping through production, and develop and govern dbt data pipelines. You will also build and optimize dashboards that deliver real-time, self-serve insights across high-priority marketing areas, drive data independence for Marketing stakeholders, and collaborate with the Marketing team and data partners to establish the AI Business Context layer for marketing use cases.

You will serve as the primary data partner for marketing managers, demand generation teams, and leadership, translating complex data insights into clear business recommendations via dashboards, memos, and presentations. You will achieve a comprehensive mastery of Airtable's marketing data models, existing pipelines, and BI tools within the first 6 months, becoming the definitive internal expert.

This is a genuinely AI-native role, requiring active, demonstrated daily use of AI coding tools such as Cursor, Claude, ChatGPT, and Gemini. You must provide specific, concrete examples of how these tools are integral to your work, moving beyond simple familiarity.

## Skills

### Required
- Expert-level SQL
- 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)
- Mandatory use of GitHub for version control in a standard development workflow

### Nice to have
- 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)