Software Engineer, Data

The shape of it

In the posting’s own words

As a Software Engineer, Data 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 it asks for · 7

• You have 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.
• You communicate with clarity and precision in written form and have experience conveying findings through graphs and visualizations.

What the job covers

• 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.

Tools and skills named

Words the posting leans on

• data23×
• business9×
• pipelines8×
• product6×
• agent5×
• understand5×
• analytics4×
• build4×
• experience4×
• platform4×
• solutions4×
• data engineering3×
• data pipelines3×
• partner3×
• stakeholders3×
• adoption2×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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