Common Room is an AI GTM Platform that provides AI agents built on comprehensive buyer intelligence. They unify all signals across the buyer journey into a continuously updated, person-level view, enabling GTM teams to identify target customers, understand their needs, and determine the optimal time to engage. The platform replaces fragmented tools with a single system designed for scale and complexity, integrating data, orchestration, and execution. Common Room has secured over $50 million in funding from leading investors like Greylock, Index, and Madrona, and is supported by operators from companies such as Figma, Stripe, Airtable, Slack, Notion, and Loom.

About the Position

Introduction

Common Room is seeking a Data Analyst / Engineer to transform billions of daily events and user actions into actionable insights. You will work within the AI GTM Platform, partnering with Product, GTM, and Leadership teams to define metrics, build datasets, and create dashboards that drive decision-making for both internal teams and customers.

Responsibilities

Transform billions of daily events and user actions into clear, actionable insights.
Partner closely with Product, GTM, and Leadership to understand needs, define metrics, and build datasets and dashboards.
Build systems to transform data for customer insights and internal product/business insights.
Scale systems using ETL pipelines, data warehouses, and modern analytics tooling.
Design and maintain clean, scalable data models.
Collaborate effectively with experienced engineers and non-technical stakeholders.
Build and maintain dashboards and reporting layers (e.g., Looker, Hex, Mode).
Ensure data quality, consistent metric definitions, and data accessibility.
Identify and participate in company-building initiatives.

Requirements

5+ years of experience, with at least 2 years in ETL pipelines and data warehouses.
Ability to operate independently and seek support when needed.
Excited by and capable of owning large backend projects.
Proven collaboration skills with engineers and non-technical stakeholders.
Good judgment on technology tradeoffs, preferring supported and stable technologies.
Experience designing systems based on customer problems, creating simple and elegant solutions.
Consideration for observability, SLA, and scalability implications while avoiding premature optimization.
Familiarity with AWS, Postgres, and Node.js.
Experience with modern data tooling such as dbt, Snowflake, and BI tools (Looker, Hex, Mode).
Ability to provide candid and respectful feedback.
Capability to manage time and priorities sustainably.
Demonstrates pride, ownership, and accountability for work.