Data Engineer, Analytics & Self-Serve Insights

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, you will be a member of the Data Science & Analytics team building the foundation to scale analytics across our organization. You will collaborate with key stakeholders in Engineering, Product, and other areas to build scalable solutions to transform data into key metrics reporting and insights. You will be responsible for ensuring teams have access to reliable, accurate metrics for consumer products from idea to implementation.

You will also lead your own projects to enable self-serve insights to help teams make data-driven decisions.

Responsibilities:

• Understand and whenever possible proactively identify the data needs of stakeholder teams in terms of key data models and reporting, and translate that into technical requirements
• Define, build and manage key data pipelines in dbt that transform raw logs into canonical datasets
• Establish high data integrity standards and SLAs to ensure timely, accurate delivery of data
• Develop insightful and reliable dashboards to track performance of core metrics that will deliver insights to the whole company
• Build foundational data products, dashboards and tools to enable self-serve analytics to scale across the company
• Closely partner with stakeholders to define and materialize metrics and analysis for new and evolving consumer products in a fast paced environment
• Influence the future roadmap of Product teams from a data systems perspective
• Become an expert in our organization’s data models and the company's data architecture

You might be a good fit if you have:

• 7+ years of experience as an Data Engineer or similar Data Science & Analytics roles, preferably partnering with Product leads to build and report on key company-wide metrics.
• A passion for the company's mission of building helpful, honest, and harmless AI.
• Expertise in building multi-step ETL jobs through tooling like dbt; proficiency with workflow management platforms like Airflow and version control management tools through Git Hub.
• Expertise in SQL and Python to transform data into accurate, clean data models
• Experience building data reporting and dashboarding in visualization tools like Hex to serve multiple cross-functional teams.
• A bias for action and urgency, not letting perfect be the enemy of the effective.
• A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.
• Experience building a Data Engineering (or similar) function at start-ups.
• A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress.
• Experience scaling own productivity and that of others by leveraging AI without sacrificing the quality of deliverables.

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

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,…