People Data Architect (Data Science)

Gen•New York, NY

5d•$170,000 - $200,000•Hybrid

About The Position

About Gen: At Gen, our mission is to create innovative and easy-to-use technology solutions that help people grow, manage, and secure their digital and financial lives. Dual-headquartered in Tempe, Arizona and Prague, Czech Republic, Gen powers Digital Freedom for nearly 500 million users in more than 150 countries through our trusted brands, including Norton, Avast, LifeLock, and MoneyLion. We serve Gen D — Generation Digital — by delivering award-winning products in cybersecurity, identity protection, online privacy, and financial wellness. We think big, innovate boldly, and operate with a shared commitment to create meaningful impact for our customers, communities, and each other. About the Role: As part of Gen’s People & Culture (P&C) organization, this role operates in an agile, product-minded HR model, partnering across sprints, squads, and centers of excellence to deliver exceptional employee experiences and power data-driven, AI-enabled decision making. The People Data Architect is the technical and strategic owner of Gen’s people data ecosystem. This role designs and maintains the data warehouse, pipelines, models, and analytics infrastructure that power accurate, trusted, and timely workforce insights across the organization. This leader brings together data engineering, business intelligence, and HR domain expertise to create scalable and governed analytics products. They manage the BI environment for people data, ensure consistent business logic, and deliver dashboards and self-service tools that enhance decision-making for People & Culture (HR, Workplace & Procurement) and business leaders. As Gen evolves toward a more digital, AI-enabled, and insight-driven operating model, this role is essential to advancing data quality, transparency, and the analytics capabilities of the P&C function.

Requirements

5+ years of experience in data engineering, BI development, workforce analytics, or a related quantitative discipline.
Hands-on experience designing and managing data warehouses, ETL/ELT pipelines, and dimensional data models.
Proficiency with SQL and modern data stack tools (Snowflake, Redshift, or similar).
Experience administering and developing in enterprise BI tools (Power BI, Tableau, or Looker).
Strong understanding of HR data structures (Workday, ATS, performance, compensation, learning, etc.).
Ability to translate business questions into data models, analytical approaches, and dashboards.
Demonstrated strengths in data governance, quality, and documentation.

Nice To Haves

Experience supporting People/HR functions in a global, multi-system environment.
Familiarity with Python or R for advanced analytics or automation.
Knowledge of machine learning concepts or predictive modeling related to workforce data.
Experience enabling self-service analytics at scale.
Exposure to AI tools or HR technology transformation initiatives.
Background in storytelling, consulting, or executive-level insights delivery.

Responsibilities

Own and evolve the end-to-end people data architecture, including warehouse environments, ETL/ELT pipelines, data models, and governance.
Maintain a single source of truth for workforce metrics with standardized definitions, consistent logic, and strong data quality controls.
Lead the development, deployment, and maintenance of dashboards, reports, and analytics products that drive actionable insights for HR and business leaders.
Enable governed, secure, and intuitive self-service BI capabilities across the P&C organization.
Partner closely with People Operations, HRBPs, CoEs, IT, and Finance to ensure data alignment, integration, reconciliation, and system optimization.
Monitor data quality, platform performance, and user experience; implement continuous improvements.
Support foundational AI-readiness by structuring and documenting clean, high-quality people data assets.
Design dimensional models and curated data sets to support reporting, predictive analytics, and workforce planning.
Build scalable ETL/ELT pipelines using modern data engineering tools (e.g., dbt, Fivetran, Airflow).
Administer the BI platform (e.g., Tableau, Power BI, Looker), including governance, permissions, semantic layers, and performance optimization.
Develop advanced analytics solutions such as headcount forecasting, attrition modeling, compensation analysis, and talent flow insights.
Transform raw data into business-ready assets, enabling reporting, storytelling and decision support for senior executives.
Establish data governance practices, including metadata, lineage, definitions, and role-based access control.
Serve as a technical advisor for emerging use cases in AI, automation, and predictive analytics within the HR ecosystem.