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Airtable is a no-code platform used by 500,000+ organizations, including 80% of the Fortune 100, to build and automate business processes. The company is evolving into an AI-native platform where customers can generate full applications and deploy AI agents directly into workflows.
As a Software Engineer, Data, you'll be a core member of the Product & AI Data Infrastructure team, responsible for designing and maintaining mission-critical data pipelines that power product analytics and business intelligence across the organization. Your work will directly support Airtable's shift toward AI-native capabilities by instrumenting AI product usage, building event pipelines for AI agents, and surfacing adoption metrics to executive stakeholders.
Key responsibilities include:
- Collaborating across engineering, data science, growth, sales, marketing, and product teams to translate business questions into scalable data solutions
- Designing and maintaining foundational business tables that simplify analysis and reporting company-wide, including AI usage metrics
- Building and enforcing consistent patterns across the data stack to ensure pipelines and tables are reliable and well-understood
- Improving the performance and reliability of the data warehouse
- Partnering with data scientists and analytics engineers to scope and deliver complex data solutions
- Using AI tools as part of your daily workflow, from LLM-assisted pipeline development to AI-powered data discovery
You'll have the unique opportunity to instrument the same platform your customers use daily, giving you early visibility into new features and the ability to influence what gets built next.
Required qualifications:
- 8+ years of professional experience designing, creating, and maintaining scalable data pipelines (Airflow experience preferred)
- Proficiency in at least one programming language, preferably Python
- Strong SQL skills with ability to write and optimize complex queries
- Deep understanding of how complex data systems fail and how to build resilience
- Genuine curiosity about AI's impact on data engineering with hands-on experimentation
- Clear written communication skills and experience with data visualization
- Passion for building systems that enhance human understanding
