Recruiting Analytics Data Engineer

Anthropic; New York, San Francisco, Seattle (NY, CA, WA); Hybrid; USD 285,000 - 380,000; Full time

Job summary

Anthropic is seeking a Recruiting Analytics Data Engineer to join our People Data Solutions team. You will design scalable data architectures, implement robust data models, and build ETL/ELT pipelines that power recruiting analytics across the company.

The role sits at the intersection of data engineering and talent analytics, working with Workday, Greenhouse, and BigQuery. Collaborate with data scientists, recruiting partners, and software engineers to translate HR concepts into trusted

Qualifications

• 5+ years in data engineering.
• Familiarity with ATS platforms (Greenhouse, Lever) and their data structures.
• Experience building semantic layers for data agents.
• Experience building data pipelines for HR data and text analytics.
• Knowledge of graph databases or network analysis libraries.
• Privacy-enhancing technologies or sensitive data handling.

Responsibilities

• Refactor and optimize BigQuery tables to a scalable data foundation.
• Design scalable data architectures and dimensional models.
• Implement data governance with documentation, lineage, quality monitoring, alerts.
• Ensure data access controls including row/column security for candidate data.
• Build ETL/ELT pipelines using dbt and BigQuery with Workday and Greenhouse data.
• Create data flows for real-time and batch processing.
• Design fault-tolerant pipelines with error handling and monitoring.
• Automate data quality checks and validation across pipelines.
• Develop semantic layers and documentation for non-technical users.
• Build data products for metrics like offer accept rate, time to fill, headcount movement.
• Partner with data scientists, engineers, and recruiting teams to model needs.
• Be an expert in BigQuery optimization and partitioning.
• Translate HR concepts into scalable data models.
• Communicate effectively with technical and business stakeholders.

Skills

BigQuery

SQL

Python

dbt

Fivetran

ETL/ELT

data governance

data modeling

data pipelines

Workday

Greenhouse

Education

Bachelor's degree

Tools

BigQuery

dbt

Fivetran

Workday

Greenhouse

Job description

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

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

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

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.

$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.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact - advancing our long-term goals of steerable, trustworthy AI - rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage:Learn aboutour policy for using AI in our application process.

We believe that AI will have a transformative impact on the world, and we’re seeking exceptional candidates who collaborate thoughtfully with Claude to realize this vision. At the same time, we want to understand your unique skills, expertise, and perspective through our hiring process. We invite you to review our AI partnership guidelines for candidates and confirm your understanding by selecting "Yes".

Voluntary Self-Identification

As set forth in Anthropic’s Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection.As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measurethe effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categoriesis as follows:

A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability.

A "recently separated veteran" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.

An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.