Senior · Удалённо · Сан-Франциско, США · Английский B2
Навыки
Airflow
Отладка и поиск ошибок
DWH
LLM
Zapier / Make / n8n
Мониторинг и observability
Python
Ещё 2
RAG
SQL
О компании и продукте
Our team is embedded in how Airtable understands itself as a business, working closely with Data Science and Analytics. What's unusual here: the platform you're instrumenting is the same one your customers use every day. When Airtable ships a new AI agent capability, you're among the first to wire it up, measure its adoption, and influence what gets built next.
Product & AI Data Infrastructure This team builds and owns the foundational data pipelines that power product analytics across Airtable. As Airtable shifts to an AI-native platform, our work increasingly involves instrumenting and measuring AI product usage, building event pipelines for AI agents, surfacing AI-native adoption metrics in core business tables, and developing AI-powered data discovery tooling, including vector search over our catalog metadata. We partner closely with product analytics, product engineering, and data infrastructure to turn business questions into well-modeled, trustworthy data.
Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes
Задачи
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
Требования
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
Compensation awarded to successful candidates will vary based on their work location, relevant skills, and experience
To learn more about our comprehensive benefit offerings, please check out Life at Airtable
For work locations in the San Francisco Bay Area, Seattle, New York City, and Los Angeles, the base salary range for this role is
For all other work locations (including remote), the base salary range for this role is
Please see our Privacy Notice for details regarding Airtable’s collection and use of personal data relating to the application and recruitment process by clicking here
For applicants that live in or have a link to Australia, please see this Privacy Collection Statement for details regarding Airtable's collection and use of personal data relating to the application and recruitment process
Stay Safe from Job Scams
All official Airtable communication will come from an @airtable.com email address
We will never ask you to share sensitive information or purchase equipment during the hiring process
If in doubt, contact us at hr@airtable.com
Learn more about avoiding job scams here
Условия
More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done
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 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
Our total compensation package also includes the opportunity to receive benefits, restricted stock units, and may include incentive compensation
196,000 — $278,100 USD
177,000 — $250,300 USD
Паспорт вакансии
История публикации
Появилась в Вакандии29 дней
Перепубликациинетпубликовалась один раз
Проверяли на источникеВидели 29 дней назад
Среди похожихНет данных274 из 30 · у похожих вакансий почти одинаковый возраст — сравнивать нечего
Откуда что взялось
Отмечено то, что вывели мы. Без пометки — значение назвал работодатель.
ГрейдSeniorвыведено из другого признака
Формат работыУдалённовычитано из текста вакансии
ГеографияСан-Франциско, СШАвычитано из текста вакансии
Зарплата≈ 17 667 USD в месяцнаша оценка, в вакансии не названа
Почему на этом месте в выдаче
Порядок выдачи объявлен контрактом: свежесть решает между днями, полнота и зарплата — внутри дня.
Полнота карточки1004 из 4 полей: грейд, формат, география, зарплата
Зарплата названа0вилки работодателя нет, показана наша оценка
Проверка Вакандии
Источники и свежесть
Тип источника
Карьерный сайт работодателя
Найдено публикаций
1
Посмотреть публикации и даты
greenhouseОсновная публикация · 2025-08-18
A
Работодатель
Airtable
11 активных вакансий · вилка работодателя указана в 18%
Вакандия показывает вакансию, но не отправляет отклик и не проверяет работодателя. Сам отклик вы оставляете на внешнем сайте — job-boards.greenhouse.io.
Признаки мошенничества
Просят предоплату, «залог» или деньги за обучение и оборудование.
Требуют код из SMS, данные банковской карты или доступ к «Госуслугам».
Быстро уводят в мессенджер и торопят с решением.
Обещают большой доход без опыта и без деталей задач.
Настоящий работодатель не просит денег и платёжных данных до трудоустройства.
Продолжить поиск
Похожие вакансии
Причина сходства указана на каждой карточке
G
Почему похожа: похожая специализация · тот же грейд