Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems. Backed by Accel, Bessemer and General Catalyst.
About the role
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 Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 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
More about this role
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.
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...
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