Recruiting Analytics Data Engineer

Anthropic•Seattle, WA

8d•$285,000 - $380,000•Hybrid

About The Position

Anthropic is seeking a Recruiting Analytics Data Engineer to join their People Data Solutions team. This role focuses on building and maintaining the data infrastructure for recruiting analytics capabilities. The individual will be the technical foundation for the recruiting analytics team, designing scalable data architectures and implementing robust data models to support evidence-based decision-making. The position is at the intersection of data engineering and recruiting analytics, involving building the technical foundation for insights into recruiting funnels, interviews, and workforce planning, while working with a team experimenting with AI to transform workforce understanding and support. Key responsibilities include Data Infrastructure & Modeling, such as refactoring and optimizing BigQuery tables for a scalable data foundation, designing data architectures and dimensional models, implementing data governance (documentation, lineage, quality monitoring, alerting), and ensuring data access controls for sensitive candidate data. Pipeline Development & Integration involves building and maintaining ETL/ELT pipelines using dbt and Google BigQuery, integrating data from HRIS (Workday) and ATS (Greenhouse), creating reliable data flows for real-time and batch processing, designing fault-tolerant pipelines with error handling and monitoring, and automating data quality checks. Analytics Engineering & Modeling includes developing semantic layers and documentation for non-technical users, building data products for key metrics (offer accept rate, time to fill, headcount movement), and partnering with stakeholders to build scalable data models.

Requirements

Expert in BigQuery including optimization and partitioning
Have built dimensional models and understand slowly changing dimensions
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

Nice To Haves

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

Responsibilities

Refactor and optimize existing BigQuery tables to create a scalable data foundation that supports and enables 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
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
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