Data Engineer, Product
Anthropic San Francisco, CA | New York City, NY | Seattle, WAEst. Est. USD 140,000–190,000 / yearSenior
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Python
- Sql
- Airflow
- Dbt
- Data Science
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 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.
Responsibilities
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
You may be a good fit if you have
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
Strong candidates may also have
Experience building a data engineering (or similar) function from the ground up in an early-stage or fast-growing environment
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 beli
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