Data Engineer (Recruiting Analytics)

• 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
• Data Infrastructure & Modeling:
• Refactor and optimize our 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
• Pipeline Development & Integration:
• Build and maintain ETL/ELT pipelines using dbt and Google BigQuery to integrate data from our 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

Benefits

• Comprehensive health, dental, and vision insurance for you and your dependents
• Inclusive fertility benefits via Carrot Fertility
• 22 weeks of paid parental leave
• Flexible paid time off and absence policies
• Mental health support for you and your dependents
• Competitive salary and equity packages
• Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant
• Retirement plans with competitive matching
• Life and income protection plans
• $500/month flexible wellness and time saver stipend
• Commuter benefits
• Annual education stipend
• Home office stipends
• Relocation support for those moving for Anthropic
• Daily meals and snacks in the office- Are an expert in BigQuery including optimization and partitioning
• Are proficient in SQL, Python, and modern tools like dbt and Fivetran
• Communicate effectively with both technical and business stakeholders
• Have built dimensional models and understand slowly changing dimensions
• Have implemented data security and privacy controls in cloud warehouses
• Can translate HR concepts into scalable data models
• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed
• Familiarity with workforce planning and predictive analytics use cases
• Previous experience in high-growth technology companies or AI/ML organizations
• Experience with building semantic layers for data agents
• Familiarity with ATS platforms (Greenhouse, Lever) and their data structures
• Have 5+ years in data engineering
• Knowledge of graph databases or network analysis libraries
• Background in privacy-enhancing technologies or sensitive data handling
• Experience building data pipelines for survey data and text analytics