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Data Engineer, Billing & Payments

San Francisco, CA | New York City, NY

Live, first seen by us 21 days ago
Pay
USD 320,000–405,000/year — pay source
Annual Salary: $320,000—$405,000 USD Logistics
The annual compensation range for this role is listed below.
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Work setting
Not stated
Employment
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Before you apply

Work authorization
Sponsors visas

What you’ll work on

Full posting

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.

  • Build and maintain dbt data models and pipelines for billing, usage and payments data

  • Own revenue data accuracy and reconciliation across billing, usage and revenue systems

  • Build dashboards and self-serve data products tracking core billing metrics

  • Share on-call and data operations duties for Finance Data Engineering pipelines

From the employer’s posting
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.
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
Build dashboards and self-serve data products that track core metrics and deliver insights across the company
Share on-call and data operations responsibilities for Finance Data Engineering pipelines

What you’ll bring

All qualifications

Core experience

  • Experience as a Data Engineer, Analytics Engineer or in a similar role
  • Experience with SQL and Python, and 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
  • Ability to prioritize and deliver practical solutions quickly

Preferred experience

  • 5+ years of experience as a Data Engineer, Analytics Engineer or in a similar role
  • 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
Qualification wording
Experience as a Data Engineer, Analytics Engineer or in a similar role
Experience with SQL and Python, and 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
Ability to prioritize and deliver practical solutions quickly
5+ years of experience as a Data Engineer, Analytics Engineer or in a similar role
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
Education & alternatives
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

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems.

In the employer’s words · Read in context

Apply at Anthropic

Posting record

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Status in our records
Live
First seen by us
Oct 14, 202621 days ago
Recorded sightings
105
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

Higher than most similar jobs

$320K–$405K against $127K–$190K, the middle half of what similar US postings state.

From 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 21

Similar jobs usually come down between day 5 and day 54.

From 10,736 similar postings that came down. Coming down is not always a hire.

Anthropic is hiring

27 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring is picking up
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • dbt
  • Airflow
Where the posting names them
- Experience as a Data Engineer, Analytics Engineer or in a similar role - Experience with SQL and Python, and building multi-step data pipelines with tools like dbt - Experience with workflow orchestration tools like Airflow, and version control with GitHub
- Build dashboards and self-serve data products that track core metrics and deliver insights across the company - Promote best practices for dbt, data modeling and SQL - Influence the Billing Engineering roadmap from a data systems perspective
- 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
- Experience with SQL and Python, and 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

Your next step

Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

About Anthropic

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.

Key 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 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
  • Promote best practices for dbt, data modeling and SQL
  • Influence the Billing Engineering roadmap from a data systems perspective
  • Build a thorough understanding of our data models and data architecture

Minimum qualifications

  • Experience as a Data Engineer, Analytics Engineer or in a similar role
  • Experience with SQL and Python, and 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
  • Ability to prioritize and deliver practical solutions quickly
  • Willingness to solve problems end to end, including work beyond the original scope
  • Ability to define next steps and keep work moving when requirements are unclear
  • Interest in Anthropic’s mission of building safe and beneficial AI

Preferred qualifications

  • 5+ years of experience as a Data Engineer, Analytics Engineer or in a similar role
  • 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.

Annual Salary:
$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 from @anthropic.com email 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.

Source details

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Pay
Annual Salary: $320,000—$405,000 USD Logistics
More source context
The annual compensation range for this role is listed below.
Location & working pattern

San Francisco, CA | New York City, NY

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.
Work authorization
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.

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