- Страна
- США
- Зарплата
- 157 100 $ – 193 600 $
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AI Analytics Engineer (Business Analytics)
Высокий балл обусловлен сильным брендом компании, конкурентной зарплатой и уникальной возможностью работать на стыке Data Engineering и AI. Позиция предлагает отличные перспективы роста в современной технологической среде.
Сложность вакансии
Роль требует сочетания навыков классического Analytics Engineering (dbt, SQL, Snowflake) и активного интереса к AI/LLM. Хотя порог входа по опыту составляет 1–4 года, высокая планка ожидается в области финансовой точности и способности работать в условиях неопределенности.
Анализ зарплаты
Предлагаемая зарплата ($157k - $193k) находится на верхней границе или даже выше рыночного уровня для специалистов с опытом 1–4 года в Сан-Франциско. Это отражает высокую ценность редкого сочетания навыков аналитики и AI.
Сопроводительное письмо
I am writing to express my strong interest in the AI Analytics Engineer position at Airtable. With a solid background in SQL and dbt, combined with a passion for the emerging AI landscape, I am excited about the opportunity to build the next generation of financial data infrastructure. My experience in developing scalable data pipelines and my proactive approach to experimenting with LLMs like Claude and ChatGPT align perfectly with Airtable's AI-first vision for analytics.
In my previous work, I have consistently focused on bridging the gap between complex data logic and business-ready insights. I am particularly drawn to this role's emphasis on creating an 'AI Business Context' layer, as I believe that structured documentation and precise context engineering are the keys to unlocking self-serve analytics. I am eager to bring my technical curiosity and builder mindset to the Strategic Finance and Accounting teams to help define how analytics evolves at Airtable.
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Описание вакансии
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.
Join Airtable as an Analytics Engineer supporting our Strategic Finance and Accounting teams, where you’ll take an AI-first approach to building the next generation of analytics infrastructure and tooling. This is a unique opportunity to shape how Finance stakeholders access and leverage data, driving real-time, self-serve insights and accelerating the adoption of AI-native analytics across Airtable.
In this role, you’ll own the canonical financial data models and analytics infrastructure that power critical metrics like ACV, ARR, billings, and revenue. You’ll build scalable data pipelines, dashboards, and AI-powered systems that enable Finance stakeholders to explore data independently and make confident decisions. If you’re passionate about data, finance, and emerging AI tooling—and want to help define how analytics evolves inside a modern software company—we’d love to meet you.
*Note on Leveling: We’re particularly interested in candidates with 1–4 years of professional experience.*
What you'll do
- Design and maintain trusted data models for core financial metrics including ACV, ARR, billings, revenue recognition, and cost allocation, managing the full lifecycle from prototyping through production
- Develop and govern dbt data pipelines, establishing data integrity standards and SLAs that ensure timely and accurate delivery of financial data across Finance and Accounting
- Build and optimize dashboards that deliver real-time, self-serve insights across key financial areas including revenue performance, expense tracking, budget variance, and forecasting accuracy
- Enable data independence for Finance stakeholders by eliminating reliance on ad-hoc data requests and manual reporting, building scalable self-service datasets in Looker and Omni for the Finance team and broader company
- Collaborate with Finance and data partners to establish the AI Business Context layer for financial use cases, translating accounting logic, metric definitions, and business rules into structured formats that AI tools can interpret accurately
- Develop tools that enable natural language access to financial data and AI-assisted reporting, empowering non-technical Finance stakeholders to explore insights independently
- Design and implement AI-powered workflows that automatically surface patterns, anomalies, and meaningful changes in financial data, delivering insights proactively to stakeholders
- Serve as the primary data partner for FP&A, Accounting, and Finance leadership, supporting strategic financial analysis and decision-making aimed at growing the business.
- Translate complex data insights into clear business recommendations through dashboards, memos, and presentations that drive action
- Drive cross-functional adoption of analytics and AI tooling, partnering with Finance stakeholders to onboard users, answer questions, triage issues, and train teams on new capabilities
- Develop deep expertise in Airtable’s financial data models, pipelines, and BI tools (dbt, Looker, Omni) within the first six months, becoming the go-to internal expert for Finance data
Who you are
- Technically curious and AI-forward: You’re energized by LLMs, prompt engineering, and the evolving landscape of AI tooling. You’ve experimented with tools like Claude/Claude Code, ChatGPT, or Manus, and you’re eager to build systems around them, not just use them.
- A builder at heart: You have a bias toward making things. Whether it’s a prototype, a pipeline, or a quick script to test an idea, you default to building rather than theorizing. You’re comfortable picking up new technical skills and exploring unfamiliar domains, especially with AI tooling accelerating what’s possible.
- Analytically grounded: You’re SQL-proficient and have experience with modern data tools (dbt, Databricks, Snowflake, or similar). You have strong intuition for when data “looks wrong” and can validate query logic and troubleshoot issues independently.
- Detail-oriented with financial rigor: You understand that financial data demands precision. You’re driven by curiosity to explore data beyond the surface, but you never sacrifice accuracy for speed.
- A clear communicator and strong writer: Context engineering is fundamentally a writing discipline. You can translate complex business logic into precise, structured documentation that both humans and LLMs can interpret.
- Business-minded: You’re genuinely curious about how the business works, how we sell, how revenue flows, what metrics matter and why. You ask “what decision does this support?” not just “is the SQL correct?”
- Thrives in ambiguity: You proactively create clarity and forward momentum, even when requirements are incomplete or rapidly changing. You own workstreams end-to-end, from scoping the problem to iterating based on feedback.
- Not married to legacy tooling:You’re more interested in what’s emerging than what’s established. You evaluate tools based on what they enable, not how long they’ve been around.
Airtable is an equal opportunity employer. We embrace diversity and strive to create a workplace where everyone has an equal opportunity to thrive. We welcome people of different backgrounds, experiences, abilities, and perspectives. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status or any characteristic protected by applicable federal and state laws, regulations and ordinances. Learn more about your EEO rights as an applicant.
VEVRAA-Federal Contractor
If you have a medical condition, disability, or religious belief/practice which inhibits your ability to participate in any part of the application or interview process, please complete our Accommodations Request Form and let us know how we may assist you. Airtable is committed to participating in the interactive process and providing reasonable accommodations to qualified applicants.
Compensation awarded to successful candidates will vary based on their work location, relevant skills, and experience.
Our total compensation package also includes the opportunity to receive benefits, restricted stock units, and may include incentive compensation. 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:
$157,100—$193,600 USD
For all other work locations (including remote), the base salary range for this role is:
$141,600—$175,100 USD
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.
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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.
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Навыки
- SQL
- dbt
- Databricks
- Snowflake
- Looker
- Omni
- Python
- LLM
- Prompt Engineering
- Financial Modeling
Возможные вопросы на собеседовании
Проверка технической экспертизы в моделировании данных для финансовых метрик.
Как бы вы спроектировали модель данных в dbt для отслеживания ARR, учитывая апгрейды, даунгрейды и отток клиентов?
Оценка опыта работы с AI-инструментами и понимания их ограничений.
Расскажите о случае, когда вы использовали LLM для автоматизации аналитической задачи. С какими трудностями в точности данных вы столкнулись?
Проверка навыков коммуникации и 'context engineering'.
Как вы объясните логику сложного финансового показателя (например, признание выручки) так, чтобы ее понял и человек, и большая языковая модель?
Оценка способности обеспечивать self-service аналитику.
Каков ваш подход к созданию семантического слоя в Looker или Omni, чтобы минимизировать количество ad-hoc запросов от финансового отдела?
Проверка бизнес-ориентированности.
Если финансовый директор просит создать дашборд по бюджетным отклонениям, какие вопросы вы зададите, чтобы убедиться, что инструмент действительно поможет в принятии решений?
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- Страна
- США
- Зарплата
- 157 100 $ – 193 600 $