Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Airflow @ 6
Communication @ 7
Data Engineering @ 6
Data Pipelines
Data Science @ 6
ETL @ 6
GitHub @ 4
Python @ 6
Reporting @ 4
SQL @ 6
dbt @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic is seeking a Data Engineer to join the Data Science & Analytics team and build the foundation for scalable analytics across the organization. The role involves collaborating with Engineering, Product, GTM, and other stakeholders to transform data into reliable metrics, reporting, and insights. You will build scalable data solutions, establish data integrity standards, and enable self-serve analytics across the company.
Responsibilities
- Understand stakeholder data needs, including key data models and reporting requirements, and translate them into technical requirements.
- Define, build, and manage data pipelines in dbt that transform raw logs into canonical datasets.
- Establish high data integrity standards and service-level agreements to ensure timely and accurate data delivery.
- Develop reliable dashboards for tracking core metrics and delivering company-wide insights.
- Build foundational data products, dashboards, and tools to enable self-serve analytics.
- Influence the future roadmap of Product and GTM teams from a data systems perspective.
- Become an expert in the organization's data models and data architecture.
Requirements
- 5+ years of experience as a Data Engineer or in a similar Data Science & Analytics role, preferably partnering with GTM and Product leads to build and report on company-wide metrics.
- Expertise in building multi-step ETL jobs and robust data models using tools such as dbt.
- Proficiency with workflow management platforms such as Airflow.
- Experience with version control tools such as GitHub.
- Expertise in SQL and Python for transforming data into accurate, clean data models.
- Experience building data reporting and dashboards using visualization tools such as Hex.
- Experience building an Analytics Data Engineering or similar function at startups.
- A bias for action, a full-stack mindset, and the ability to work effectively in ambiguity.
- Strong initiative and communication skills.
- Bachelor's degree or an equivalent combination of education, training, and experience. The field of study must be relevant to the role through coursework, training, or professional experience.
Benefits
- Competitive compensation and benefits.
- Optional equity donation matching.
- Generous vacation and parental leave.
- Flexible working hours.
- Collaborative office space.
- Visa sponsorship support, with an immigration lawyer available to assist. Sponsorship availability may vary by role and candidate.
The role follows a location-based hybrid policy, with staff expected to work from one of Anthropic's offices at least 25% of the time. The annual salary range is $320,000–$405,000 USD.
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