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Analytics Engineer, Product Analytics

Airtable LogoAirtable
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Salary

$143,600 - $177,200

Location

San Francisco, CA; New York City, NY

As an Analytics Engineer at Airtable, you’ll play a pivotal role in shaping our product strategy through data. You’ll design, implement, and maintain robust data pipelines and analytics tools that empower our teams to make informed decisions. This is a unique opportunity to own critical analytics infrastructure, collaborate with cross-functional partners, and directly influence the direction of our product. If you’re passionate about transforming data into actionable insights and want to make a tangible impact at scale, we’d love to meet you.

What you'll do

  • Own and maintain core product data pipelines across tools such as dbt, Databricks, Looker, and Omni Analytics, ensuring reliability and scalability
  • Build and refine dashboards that deliver self-serve, real-time insights for high-priority product areas
  • Partner with product and engineering teams to define tracking requirements, implement instrumentation, validate data, and deliver launch-specific dashboards or reports
  • Establish trusted partnerships with product managers, engineers, analysts, and leadership, serving as the go-to resource for product data insights and technical guidance
  • Lead analytics engineering efforts for high-impact product launches, including documentation of tracking plans, launch pipelines, and post-launch reporting
  • Participate in or lead cross-functional projects where analytics engineering contributions directly influence product strategy decisions

Who you are

  • Bachelor’s degree in computer science, data science, mathematics/statistics, or a related field (or related experience)
  • 3–5 years of experience working with data, with at least 1 year partnering with product stakeholders
  • Curiosity and fluency with AI/LLM tools (ChatGPT, Claude, Cursor, etc.) applying them to accelerate data exploration, automate workflows, and enhance analytics productivity
  • Experience in SaaS, consumer tech, or data-driven product environments
  • Proficiency with SQL and data modeling best practices (e.g., dbt, Databricks, Snowflake, BigQuery)
  • Experience with BI tools and BI modeling best practices (e.g., Looker, Omni Analytics, Tableau, Mode, Hex)
  • Understanding of user funnels, retention metrics, and growth analytics
  • Strong ability to ensure data accuracy, reliability, and consistency
  • Ability to translate business questions into analytical approaches, interpret results, and communicate actionable insights
  • Knowledge of product analytics tracking frameworks (e.g., Segment, Amplitude, Mixpanel, GA4) and event taxonomy design
  • Familiarity with A/B testing design, execution, and analysis

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