Recruiting Analytics Data Engineer

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

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 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

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 listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:

$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. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

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.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit  anthropic.com/careers  directly for confirmed position openings.

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