Data Engineer, Product

San Francisco, CA | New York City, NY | Seattle, WA · San Francisco · USD 320,000-405,000 / year · Hybrid · Posted Oct 9, 2026

At a glance

Workplace: Hybrid
Location: San Francisco, CA | New York City, NY | Seattle, WA · San Francisco
Salary: USD 320,000-405,000 / year · Base salary
Visa sponsorship: Visa sponsorship available

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.

As a Data Engineer on the Data Science & Analytics team, you'll build the foundation that lets analytics scale across Anthropic.
You'll partner with Engineering, Product and other teams to turn raw data into reliable metrics, reporting and insights, and you'll make sure teams have accurate metrics for our consumer products from idea to launch.
You'll also lead your own projects that make self-serve insights possible, so teams can make data-driven decisions.

Understand, and where possible anticipate, the data needs of partner teams, and translate them into data models, reporting and technical requirements
Define, build and manage key dbt pipelines that turn raw logs into canonical datasets
Set data integrity standards and SLAs so data is delivered on time and accurately
Build reliable dashboards that track core metrics and share insights across the company
Build foundational data products, dashboards and tools that let self-serve analytics scale
Partner with stakeholders to define and materialize metrics and analysis for new and evolving consumer products
Shape Product teams' roadmaps from a data systems perspective
Become an expert in our data models and data architecture

Significant experience as a Data Engineer or in a similar Data Science & Analytics role, ideally partnering with Product leads to build and report on company-wide metrics
A passion for Anthropic's mission of building helpful, honest and harmless AI
Expertise building multi-step ETL jobs with tools like dbt, plus experience with workflow tools like Airflow and version control through GitHub
Expertise in SQL and Python for turning data into accurate, clean data models
Experience building reporting and dashboards in tools like Hex that serve multiple cross-functional teams
A bias for action, and a sense of when "good enough" beats perfect
An end-to-end mindset: you take ownership of solving a problem fully, even when that means picking up work beyond your usual scope
Comfort with ambiguity, and a habit of creating clarity and forward progress
Experience using AI to scale your own productivity and your team's without lowering the quality of the work

Experience building a data engineering (or similar) function from the ground up in an early-stage or fast-growing environment

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