Data Engineer, GTM

Details

As a Data Engineer on the Data Science & Analytics team, you will build the data foundation for Anthropic’s quote-to-cash lifecycle: the path a deal takes from opportunity through revenue. You will design canonical data models so that Sales, Deal Desk, Order Management, Revenue Operations, and Finance work from one governed, auditable definition of what was sold, on what terms, and where each deal stands. You will partner closely with DS&A and with GTM and Finance systems teams that own Salesforce, CPQ, and billing to make quote-to-cash data reliable, well-modeled, and self-serve as the business scales.

Responsibilities

• Understand the data needs of Deal Desk, Order Management, Revenue Operations, Finance, and Sales systems teams, and translate them into technical requirements.
• Design, build, and own data models that transform raw Salesforce, CPQ, and billing data into canonical datasets.
• Establish high data integrity standards and SLAs to ensure timely and accurate data delivery.
• Partner with Salesforce, CPQ, and billing engineers on upstream schema changes, new fields, and ingestion so the warehouse faithfully mirrors systems of record.
• Build foundational data products, dashboards, and tools to enable self-service analytics across GTM teams.
• Influence stakeholder roadmaps from a data perspective and become the expert on Anthropic’s GTM data models and architecture.

Requirements

• 5+ years of experience as a Data Engineer, Analytics Engineer, or in a similar Data Science & Analytics role, ideally partnering with GTM, Revenue Operations, or Finance teams.
• A passion for Anthropic’s mission of building helpful, honest, and harmless AI.
• Hands-on experience modeling Salesforce data and at least one adjacent quote-to-cash system, such as CPQ, contract lifecycle management, billing and invoicing, or ERP.
• Expertise in building multi-step ETL jobs and robust data models through tooling such as dbt.
• Proficiency with workflow management platforms such as Airflow and version control tools through GitHub.
• Expertise in SQL and Python to transform data into accurate, clean data models.
• Experience building data reporting and dashboards in visualization tools such as Hex for multiple cross-functional teams.
• A bias for action and urgency, with the ability to avoid letting perfect be the enemy of effective.
• A full-stack mindset and willingness to solve problems end-to-end, including outside the original job description.
• Experience building an Analytics Data Engineering or similar function at startups.
• A strong disposition to thrive in ambiguity, take initiative, create clarity, and drive progress.

Education and Experience

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience.
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience.
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position.

Compensation

• Annual salary: $320,000–$405,000 USD.

Benefits and Logistics

• Location-based hybrid policy: Staff are expected to work from one of Anthropic’s offices at least 25% of the time, although some roles may require more office time.
• Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office space for collaboration.
• Anthropic sponsors visas where possible and makes every reasonable effort to obtain a visa for candidates who receive an offer. The company retains an immigration lawyer to provide assistance.