Data Engineer, GTM
Build the data foundation for Anthropic’s quote-to-cash lifecycle as a Data Engineer on the Data Science & Analytics team.
Posted by employer 1 month ago
First seen on Joblaze 1 month ago
Last verified on the company career page 18 hours ago
What you'll build
- Understand data needs of various teams
- Design and build data models
- Establish data integrity standards
- Partner with engineers on schema changes
- Build foundational data products and dashboards
Must have
- 5+ years of experience as a Data Engineer
- Hands-on experience modeling Salesforce data
- Expertise in SQL and Python
- Experience building multi-step ETL jobs
Nice to have
- Experience with CPQ or billing systems
- Experience building data reporting in visualization tools
- A passion for building helpful AI
- Experience in start-ups
Practical constraints
- Currently, staff must be in the office at least 25% of the time
Requirements
- Experience
- 5+ years
- Education
- Bachelor's degree
- Visa
- Sponsorship available
Benefits
Joblaze summary
In the role of Data Engineer on the Data Science & Analytics team at Anthropic, the individual will focus on developing the data infrastructure that supports the company's quote-to-cash processes, ensuring that various teams have access to accurate and well-structured data. Key skills include expertise in Salesforce data modeling, proficiency in SQL and Python, and experience with ETL processes and data visualization tools. This position is suited for someone with over five years of experience in data engineering, particularly in a startup environment, who can navigate ambiguity and drive initiatives forward.
Joblaze insights
- Listed about a month ago — first seen on Joblaze September 10, 2026. Last confirmed on Anthropic's careers page October 26, 2026.
- Salary band is above the typical range for Data Engineering roles (median ~$180,656).
- Starts above 96% of 28 comparable mid data engineering roles in United States that list Python we track (median $125,000 across 15 companies). See Python salary trends
- Python appears in 70.1% of 77 comparable mid data engineering roles in United States; Salesforce appears in 5.2% of 77 comparable mid data engineering roles in United States.
Quick facts
- Is the Data Engineer, GTM role remote?
- It's hybrid — Anthropic expects some on-site time in San Francisco, CA | New York City, NY.
- What's the salary range?
- Anthropic lists $320,000–$405,000 for this role.
- How much experience is required?
- At least 5 years of relevant experience for this Data Engineer, GTM role.
- Where is the role based?
- Anthropic is hiring for this position in San Francisco, CA | New York City, NY.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Airflow, CPQ, ETL, GitHub, Hex, Python.
- Does Anthropic sponsor work visas for this role?
- Yes — the posting indicates visa sponsorship is available for the right candidate.
- What seniority level is this role?
- Anthropic targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Data Engineer, GTM role at Anthropic.
From the original posting
About Anthropic
About the Role
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 the 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 who own Salesforce, CPQ and billing to make quote-to-cash data reliable, well-modeled and self-serve as our 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, accurate delivery of data
- Partner with Salesforce, CPQ and billing engineers on upstream schema changes, new fields and ingestion so the warehouse faithfully mirrors the systems of record
- Build foundational data products, dashboards and tools to enable self-serve analytics to scale across GTM teams
- Influence stakeholder roadmaps from a data perspective, and become the expert on Anthropic’s GTM data models and architecture
You might be a good fit if you have
- 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 the company's mission of building helpful, honest, and harmless AI.
- Hands-on experience modeling Salesforce data and at least one adjacent quote-to-cash system: CPQ, contract lifecycle management, billing and invoicing, or ERP.
- Expertise in building multi-step ETL jobs, building robust data models through tooling like dbt; proficiency with workflow management platforms like Airflow and version control management tools through GitHub.
- Expertise in SQL and Python to transform data into accurate, clean data models.
- Experience building data reporting and dashboarding in visualization tools like Hex to serve multiple cross-functional teams.
- A bias for action and urgency, not letting perfect be the enemy of the effective.
- A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.
- Experience building an Analytics Data Engineering (or similar) function at start-ups.
- A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress.
The annual compensation range for this role is listed below.
Logistics
Standard company text repeated across Anthropic's postings is omitted here.