Recruiting Analytics Data Engineer

United States Digital Space LLC; New York (NY); Hybrid; USD 285,000 - 380,000; Full time

Job summary

United States Digital Space LLC is hiring a Recruiting Analytics Data Engineer to join the People Data Solutions team and build the data infrastructure powering recruiting analytics. You'll refactor BigQuery tables, design scalable data models, and implement governance and security while enabling AI-driven insights for hiring and workforce planning across the company.

Work with data scientists, software engineers, and recruiting teams to deliver trusted data products for time-to-fill,

Qualifications

• Expert in BigQuery including optimization and partitioning.
• Built dimensional models and understand slowly changing dimensions.
• Proficient in SQL, Python, and dbt and Fivetran.
• Implemented data security and privacy controls in cloud warehouses.
• Translate HR concepts into scalable data models.
• Communicate effectively with technical and business stakeholders.

Responsibilities

• Refactor and optimize BigQuery tables to support AI-driven insights.
• Design scalable data architectures and dimensional models for self-serve analytics.
• Implement data governance with documentation, lineage tracking, quality monitoring, and alerts.
• Ensure data access controls including row/column security for sensitive data.
• Build and maintain ETL/ELT pipelines using dbt and BigQuery from Workday/Greenhouse.
• Develop semantic layers and data products for key metrics like time-to-fill and headcount movement.
• Collaborate with data scientists, engineers, and recruiting teams on scalable models.

Skills

BigQuery optimization

SQL

Python

Data security

HR data modeling

Stakeholder communication

Education

Bachelor’s degree

Tools

dbt

Fivetran

Workday

Greenhouse

Lever

Job description

About the company

the company’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 the company.

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 responsibilitiesData 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

LogisticsMinimum 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 the company 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