Data Engineer, Billing & Payments

anthropic; San Francisco, New York (CA, NY); On-site; USD 320,000 - 405,000; Full time

Job summary

Anthropic is seeking a Data Engineer to join the Finance Data Engineering team focused on Billing & Payments. You’ll build scalable data pipelines in dbt, own revenue data accuracy, and create self-serve insights with dashboards for cross-functional teams.

Bring 5+ years in data/analytics engineering, expertise in SQL and Python, experience with Airflow and GitHub, and familiarity with billing concepts. You’ll influence the data architecture and drive data quality across billing systems.

Qualifications

• 5+ years of experience as a Data Engineer, Analytics Engineer or in a similar role.
• Expertise in SQL and Python, and in building multi-step data pipelines with tools like dbt.
• Experience with workflow orchestration tools like Airflow, and version control with GitHub.
• Familiarity with billing concepts such as invoicing, payments, credits, refunds and subscriptions, and experience working with data from billing systems.
• Experience building dashboards and reporting in tools like Hex for multiple cross-functional teams.
• A bias for action and urgency, without letting perfect be the enemy of the effective.
• A full-stack mindset: you do what it takes to solve a problem end to end, even when it goes beyond the original scope.
• Comfort with ambiguity, and the initiative to create clarity and keep work moving.
• A passion for Anthropic's mission of building helpful, honest and harmless AI

Responsibilities

• Design, build and maintain data models and pipelines in dbt that transform raw billing, usage and payments data into canonical datasets.
• Own revenue data accuracy and reconciliation across systems.
• Define success metrics for billing systems and build data models and monitoring.
• Set high data integrity standards and SLAs for timely, accurate delivery of billing and revenue data.
• Share on-call and data operations responsibilities for Finance Data Engineering pipelines.
• Build dashboards and self-serve data products that track core metrics across the company.
• Champion best practices for dbt, data modeling and SQL.
• Influence the Billing Engineering roadmap from a data systems perspective.
• Become an expert in our data models and data architecture.

Skills

SQL

Python

dbt

Airflow

GitHub

Billing data

Dashboards

Data modeling

Data pipelines

Financial metrics

Education

Bachelor's degree

Tools

Hex

GitHub

Job description

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role
As a Data Engineer supporting Billing & Payments Engineering, you'll join the Finance Data Engineering team and build the foundation for accurate, scalable billing and revenue data across Anthropic. You'll work closely with Billing Engineering, Finance and Accounting, as well as Product and other partners, to turn billing and payments data into reliable metrics, reporting and insights. You'll make sure teams have trustworthy data that scales with our growth, and you'll lead your own projects to enable self-serve insights that help teams make data-driven decisions.

Responsibilities:

• Partner with Billing Engineering, Finance and Accounting to understand their data and reporting needs, and translate them into technical requirements
• Design, build and maintain data models and pipelines in dbt that transform raw billing, usage and payments data into canonical datasets
• Own revenue data accuracy and reconciliation, making sure billing, usage and revenue data tie out across systems
• Define success metrics for billing systems, and build the data models and monitoring to track them
• Set high data integrity standards and SLAs for timely, accurate delivery of billing and revenue data
• Share on-call and data operations responsibilities for Finance Data Engineering pipelines
• Build dashboards and self-serve data products that track core metrics and deliver insights across the company
• Champion best practices for dbt, data modeling and SQL
• Influence the Billing Engineering roadmap from a data systems perspective
• Become an expert in our data models and data architecture

You may be a good fit if you have:

• 5+ years of experience as a Data Engineer, Analytics Engineer or in a similar role
• Expertise in SQL and Python, and in building multi-step data pipelines with tools like dbt
• Experience with workflow orchestration tools like Airflow, and version control with GitHub
• Familiarity with billing concepts such as invoicing, payments, credits, refunds and subscriptions, and experience working with data from billing systems
• Experience building dashboards and reporting in tools like Hex for multiple cross-functional teams
• A bias for action and urgency, without letting perfect be the enemy of the effective
• A full-stack mindset: you do what it takes to solve a problem end to end, even when it goes beyond the original scope
• Comfort with ambiguity, and the initiative to create clarity and keep work moving
• A passion for Anthropic's mission of building helpful, honest and harmless AI

Strong candidates may also have:

• Experience partnering with billing, finance or accounting teams on revenue metrics and reconciliation
• Experience building an analytics or data engineering function from an early stage

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

$320,000 - $405,000 USD

Logistics

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

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship:We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you [e-mail] addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage:Learn about our policy for using AI in our application process.

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiringprocess or thereafter. Any information that you do provide will be recorded and maintained in aconfidential file.

As set forth in Anthropic’s Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measurethe effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categoriesis as follows:

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