Software Engineer, Data
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.
What this role actually needs.
Software Engineer, Data at Airtable in San Francisco. UpJobz keeps this listing high-signal for applicants targeting serious high-tech roles across the United States, Canada, and Mexico. 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.
Day-to-day expectations
A clear list of the work this role is designed to cover.
- Work across our engineering organization and stakeholders from data science, growth, sales, marketing, and product to understand the data needs of the business and produce pipelines, data marts, and other solutions that enable better decision-making.
- Design and maintain our foundational business tables in order to simplify analysis and reporting across the entire company, including AI usage metrics surfaced to executive stakeholders.
- Use AI tools as a daily part of how you work, from LLM-assisted pipeline development and debugging to exploring our catalog through AI-powered discovery, and bring a curiosity for where this tooling is heading next.
- Build and enforce a pattern language across our data stack, ensuring pipelines and tables are consistent, accurate, and well-understood.
- Continue to improve the performance and reliability of our data warehouse.
- Partner with data scientists, analytics engineers, and business stakeholders to translate ambiguous business questions into well-scoped data solutions.
What a strong candidate brings
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- You have 3-8+ 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 it can go wrong, and you build with that in mind.
- You are proficient in at least one programming language (preferably Python) and are willing to pick up others as the work demands.
- You are highly effective with SQL and understand how to write and tune complex queries.
- You're genuinely curious about how AI is reshaping data engineering and you're actively experimenting, not just watching from the sidelines. Whether that's using LLMs to write and debug pipelines faster, thinking through how to model agent behavior as data, or exploring what smarter data discovery could look like, you bring enthusiasm for figuring it out.
- You're passionate and thoughtful about building systems that enhance human understanding.
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