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About the Role

As the Data Engineering Manager at Airtable, you will lead the GTM & Business Data Engineering team, which owns the datasets powering go-to-market and business operations. Your team builds business-critical pipelines and core tables for AI usage metrics, maintains data models for RevOps, Marketing, and Finance, and increasingly uses AI tools like Claude skills and AI context guidance. You will set the technical bar, shape the team's AI craft, manage team operations, and partner with company leaders on data strategy. This role is unique as the platform you measure and build on is the same one customers use daily, allowing your team to instrument, understand adoption, and shape new AI agent capabilities.

Responsibilities

Lead and develop a team of data engineers, ensuring team health and technical standards.
Establish and enforce team standards and operational procedures for pipelines, tables, and naming consistency.
Lead on-call, incident response, monitoring, and code review standards.
Drive system reliability by setting and achieving measurable goals, including SLAs for data landing time and accuracy.
Treat data as a product, enhancing data models for AI billings and usage with built-in quality, observability, and trust.
Shape the team's use of AI tools like Claude Code and Hyperagent to achieve significant time savings in pipeline development, debugging, and on-call tasks.
Partner with cross-functional leaders to translate ambiguous business questions into well-scoped data solutions.
Translate engineering work into business outcomes and advocate for strategic investments.

Requirements

2+ years managing a data, analytics, or platform engineering team with a track record of growing engineers and delivering outcomes.
10+ years building scalable data pipelines, preferably with Airflow.
Proficiency in Python.
Highly effective with SQL, including tuning complex queries.
Strong instincts for data system stability, operationalizing SLAs, observability, and incident reduction.
Ability to treat data as a product, designing for quality, trust, and stakeholder needs.
Experience as an AI-native builder, utilizing AI tools (e.g., Claude skills, LLM-assisted pipeline work, automated PR fixes, AI-powered discovery) as a core collaborator.
Clear and precise communication skills, capable of translating technical context for executives and telling stories with data.

Skills

Airflow
Python
SQL
Claude Code
Hyperagent
LLM-assisted pipeline work
Automated PR fixes
AI-powered discovery

Location

San Francisco
New York City

Work Type

Hybrid

Experience Level

2+ years managing a data, analytics, or platform engineering team
10+ years building scalable data pipelines

Salary/Compensations

$261,900—$339,900 USD (San Francisco Bay Area, Seattle, New York City, Los Angeles)
$235,700—$305,900 USD (Other locations, including remote)

Benefits

Benefits
Restricted stock units
Incentive compensation

About the Company

Airtable is a no-code app platform empowering organizations to accelerate critical business processes.
Over 500,000 organizations, including 80% of the Fortune 100, rely on Airtable.
Airtable is passionate about democratizing software creation, enabling powerful and flexible tool building without writing code.
The platform is shifting to an AI-native model, allowing customers to generate full apps and deploy AI agents directly into their workflows.

Equal Opportunity

Airtable is an equal opportunity employer, embracing diversity and striving for a workplace where everyone thrives.
All qualified applicants 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 laws.
VEVRAA-Federal Contractor.
Airtable is committed to providing reasonable accommodations to qualified applicants with medical conditions, disabilities, or religious beliefs/practices.