Data Engineer — GTM Revenue Data & Self-Serve Analytics

Engg; San Francisco, New York (CA, NY); Hybrid; USD 320,000 - 405,000; Full time

Job summary

Anthropic is seeking a Data Engineer to build the data foundation for the quote-to-cash lifecycle, aligning Salesforce, CPQ, and billing data into a governed dataset. You will work with Sales, Deal Desk, Finance, and Revenue Operations to enable reliable analytics across GTM functions.

In this role, you’ll design canonical data models, own ETL pipelines, and partner with engineering teams to keep data in sync with systems of record while promoting data quality and self-serve analytics across the

Qualifications

• 5+ years of experience as a Data Engineer, Analytics Engineer, or similar role.
• Experience modeling Salesforce data and adjacent quote-to-cash systems (CPQ, billing, invoicing, or ERP).
• Expertise in building multi-step ETL jobs and robust data models using dbt; proficient with Airflow and GitHub.
• Proficiency in SQL and Python to transform data into clean models; able to build dashboards in visualization tools.

Responsibilities

• Understand data needs of Deal Desk, Order Management, Revenue Ops, Finance, and Sales teams and translate into technical requirements.
• Design, build and own data models that transform raw Salesforce, CPQ, and billing data into canonical datasets.
• Establish data integrity standards and SLAs for timely, accurate data delivery.
• Collaborate with Salesforce, CPQ, and billing engineers on schema changes to mirror systems of record.
• Build foundational data products, dashboards and self-serve analytics for GTM teams.
• Influence stakeholder roadmaps and become the expert on Anthropic’s GTM data models and architecture.

Skills

SQL

Python

dbt

Airflow

GitHub

Salesforce data

Data warehousing

Analytics dashboards

Stakeholder communication

Education

Bachelor's degree

Tools

Salesforce

CPQ

dbt

Airflow

Hex

git

Job description

Anthropic is seeking a Data Engineer to build the data foundation for the quote-to-cash lifecycle, aligning Salesforce, CPQ, and billing data into a governed dataset. You will work with Sales, Deal Desk, Finance, and Revenue Operations to enable reliable analytics across GTM functions.

In this role, you’ll design canonical data models, own ETL pipelines, and partner with engineering teams to keep data in sync with systems of record while promoting data quality and self-serve analytics across the