Data Engineer

Anthropic; San Francisco (CA); Hybrid; USD 275,000 - 355,000; Full time

Job summary

Anthropic in San Francisco is looking for an experienced Analytics Engineer to join the Data Science & Analytics team. In this role, you will collaborate with stakeholders to build scalable solutions that transform data into reliable metrics and insights.

The ideal candidate has over 5 years of experience in analytics and data engineering, with a passion for the company's mission of creating helpful, honest AI. The position offers a competitive salary of $275,000-$355,000, with benefits and equity included.

Qualifications

• 5+ years of experience in Analytics Data Engineering or related roles.
• Expertise in multi-step ETL jobs and data transformation.
• Experience with data reporting and dashboarding.

Responsibilities

• Translate stakeholder data needs into technical requirements.
• Build and manage data pipelines in dbt.
• Develop dashboards to track company performance metrics.

Skills

SQL

Python

ETL with dbt

Data visualization tools like Hex

Workflow management platforms like Airflow

Education

Bachelor's degree in a related field

Tools

GitHub

Job description

About the Role

As an Analytics Engineer, you will be an early 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, GTM 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 that can scale with our company’s growth. You will also lead your own projects to enable self-serve insights to help teams make data-driven decisions.

Responsibilities

• Understand 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
• Influence the future roadmap of Product and GTM 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

• 5+ years of experience as an Analytics Data Engineer or similar Data Science & Analytics roles, preferably partnering with GTM and 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 GitHub.
• 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 an Analytics Data Engineering (or similar) function at start-ups.
• A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress.

Compensation

Annual Salary: $275,000-$355,000 USD

The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.

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. If we make you an offer, we will make every reasonable effort to get you a visa.