Description
About the role
We are seeking a Recruiting Analytics Data Engineer to join our People Data Solutions team, focusing on building and maintaining the data infrastructure that powers our recruiting analytics capabilities. You'll be the technical foundation for our recruiting analytics team, designing scalable data architectures and implementing robust data models that enable evidence-based decision-making across Anthropic.
This role sits at the intersection of data engineering and recruiting analytics - you'll build the technical foundation for insights about recruiting funnels, interviews, and workforce planning while working with a team that's actively experimenting with AI to transform how we understand and support our workforce.
Key responsibilities
Data Infrastructure & Modeling
- Refactor and optimize existing BigQuery tables to create a scalable data foundation that supports AI-driven data insights across the company
- Design scalable data architectures and build dimensional models that transform raw HR data into trusted, reusable datasets for self-serve analytics while maintaining performance
- Implement data governance including documentation, lineage tracking, quality monitoring, and proactive alerting systems
- Ensure appropriate data access controls including row and column-level security for sensitive candidate data
Pipeline Development & Integration
- Build and maintain ETL/ELT pipelines using dbt and Google BigQuery to integrate data from HRIS (Workday), ATS (Greenhouse), and internal tools
- Create reliable data flows that handle both real-time needs and batch processing requirements
- Design fault-tolerant data pipelines with proper error handling and monitoring to ensure data freshness
- Automate data quality checks and validation across all pipelines
Analytics Engineering & Modeling
- Develop semantic layers and comprehensive documentation that make complex recruiting data accessible to non-technical users
- Build data products that standardize key metrics like offer accept rate, time to fill, and headcount movement
- Partner with data scientists, software engineers, recruiting teams, and various other stakeholders to build scalable data models that serve needs across the company
Minimum qualifications
- Are an expert in BigQuery including optimization and partitioning
- Have built dimensional models and understand slowly changing dimensions
- Are proficient in SQL, Python, and modern tools like dbt and Fivetran
- Have implemented data security and privacy controls in cloud warehouses
- Can translate HR concepts into scalable data models
- Communicate effectively with both technical and business stakeholders
Preferred qualifications
- Have 5+ years in data engineering
- Familiarity with ATS platforms (Greenhouse, Lever) and their data structures
- Experience with building semantic layers for data agents
- Experience building data pipelines for survey data and text analytics
- Knowledge of graph databases or network analysis libraries
- Background in privacy-enhancing technologies or sensitive data handling
- Previous experience in high-growth technology companies or AI/ML organizations
- Familiarity with workforce planning and predictive analytics use cases
The annual compensation range for this role is $285,000-$380,000 USD.
Logistics
- 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, 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.