Why This Job is Featured on The SaaS Jobs
This Data Engineer role stands out in the SaaS landscape because it sits at the intersection of product analytics and platform evolution at a company positioning itself as AI-native. Airtable’s focus on app creation and deploying AI agents implies a data environment where instrumentation, measurement, and feedback loops directly influence how the product is built and improved, not just how it is reported.
From a SaaS career perspective, the mandate to own “foundational business tables,” improve warehouse reliability, and establish a pattern language across the data stack maps to durable, cross-company competencies. Building trusted pipelines and data marts that serve growth, product, and go-to-market teams develops the kind of data governance and stakeholder partnership experience that transfers well across subscription businesses, where consistent definitions and timely metrics are operational necessities.
The role is best suited to an engineer who prefers end-to-end ownership and is comfortable translating ambiguous business questions into robust datasets. It will fit someone who enjoys rigorous SQL work, pragmatic software engineering in Python, and the operational discipline required to keep pipelines dependable as usage and reporting demands expand.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
At Airtable, we’re passionate about democratizing software creation—empowering anyone to build powerful, flexible tools without writing code. With our shift to an AI-native platform, customers can now generate full apps and deploy AI agents directly into their workflows. Data engineering plays a critical role in this evolution by delivering the insights our teams rely on to improve user experience, measure agent impact, and understand how the business is performing at scale.
As one of the data engineers at Airtable, you'll make an enormous contribution to our data engineering efforts. You'll design and own mission-critical data pipelines to enable decision-making, partner with company leaders to create scalable data solutions, and launch innovative alerting and visualization solutions.
What you'll do
- Work between our engineering organization and stakeholders from our data science, growth, sales, marketing, and product teams, to understand the data needs of the business and produce pipelines, data marts, and other data solutions that enable better product and growth decision-making.
- Design and update our foundational business tables in order to simplify analysis across the entire company.
- Continue to improve the performance and reliability of our data warehouse.
- Build and enforce a pattern language across our data stack, ensuring that our data pipelines and tables are consistent, accurate, and well-understood.
Who you are
- You have 5+ years of professional experience designing, creating and maintaining scalable data pipelines, preferably in Airflow.
- You've wrangled enough data to understand how often the complex systems that produce data can go wrong.
- You are proficient in at least one programming language (preferably Python), and are willing to become effective in others as needed to get your job done.
- You are highly effective with SQL and understand how to write and tune complex queries.
- You're passionate and thoughtful about building systems that enhance human understanding.
- You communicate with clarity and precision in written form; experience communicating with graphs and plots.
