Data Engineer, Product
Apache Airflow
Data
Data Analysis
Data Analytics
Data Architecture
Data Build Tool
Data Engineer
Data Engineering
Data Integration
Data Management
Data Modeling
Data Operations
Data Pipeline
Data Pipelines
Data Platform
Data Processing
Data Transforms
Data Warehouse
Database
Databases
Dbt
ETL
Hex
Information Technology (IT)
Reporting and Analytics
SQL
Job Description
As a Data Engineer on the Data Science & Analytics team, you will help establish the data foundation that powers analytics for consumer products. The role focuses on transforming raw data into trusted metrics, reporting outputs, and insights that teams can use to make decisions.
What You’ll Do
- Assess and anticipate partner teams’ data needs, then convert those needs into data models, reporting requirements, and technical specifications
- Define, build, and operate key dbt pipelines that convert raw logs into canonical datasets
- Set data integrity standards and SLAs to support delivery on time and with accurate results
- Create dependable dashboards that monitor core metrics and distribute insights across the organization
- Develop foundational data products, dashboards, and tools that enable self-serve analytics to scale
- Collaborate with stakeholders to define and materialize metrics and analysis for existing and new consumer products
- Contribute to Product teams’ roadmaps from a data systems perspective
- Build deep expertise in Anthropic data models and overall data architecture
Required Qualifications
- Significant experience as a Data Engineer or in a comparable Data Science & Analytics role, ideally working with Product leads on company-wide metrics
- A commitment aligned with Anthropic’s mission of building helpful, honest, and harmless AI
- Proficiency creating multi-step ETL jobs using dbt, along with experience using workflow tools such as Airflow and version control via GitHub
- Expertise in SQL and Python to build clean, accurate data models
- Experience creating reporting and dashboards in tools like Hex for cross-functional stakeholders
- A strong execution mindset and an ability to determine when “good enough” is preferable to perfection
- An end-to-end approach that includes taking ownership beyond the usual scope to fully solve a problem
- Comfort working in ambiguous environments, with a practice of creating clarity and forward movement
- Experience using AI to improve personal and team productivity without reducing work quality
Technologies
- dbt
- Airflow
- GitHub
- SQL
- Python
- Hex
Education
Bachelor’s degree or an equivalent combination of education, training, and/or experience.
Compensation
The annual compensation range for this role is USD 320,000 - 405,000.
- Annual Salary: $320,000—$405,000 USD
Benefits
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation
- Parental leave
- Flexible working hours
- Lovely office space in which to collaborate with colleagues
Additional Considerations
- Experience building a data engineering function (or similar) from the ground up in an early-stage or fast-growing environment
Location and Logistics
- Location: New York, NY (hybrid)
- Location-based hybrid policy: expected to be in one of the offices at least 25% of the time
- Visa sponsorship: offered (not able to sponsor every role/candidate); reasonable effort if making an offer, with an immigration lawyer retained to help
- Field of study: a field relevant to the role as demonstrated through coursework, training, or professional experience
- Minimum years of experience: correlated with internal job level requirements for the position
- Encouragement to apply: encouraged even if you do not meet every qualification
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