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 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.
Who you are
- 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.
- 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).
- 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.
Airtable is an equal opportunity employer. We embrace diversity and strive to create a workplace where everyone has an equal opportunity to thrive. We welcome people of different backgrounds, experiences, abilities,