People Intelligence Architect

Block•Bay Area, CA, United States of America, CA

1d•$142,600 - $257,600•Remote

About The Position

Block is seeking a cross-disciplinary builder to own the integration of its people data ecosystem, from raw data pipelines to predictive models and actionable AI-driven workflows. This role goes beyond traditional People Analytics, focusing on designing and constructing an end-to-end system that ensures People data is reliable, intelligent, and increasingly autonomous. As a senior individual contributor, the focus is on technical leadership, architectural design, production code development, and setting the technical standard for People data and AI within the company. The position operates at the intersection of data engineering, data science, people analytics, and agentic AI, requiring fluency in each area to connect the system and hands-on capability to build the necessary components.

Requirements

8+ years of relevant experience
Proven experience building data pipelines (SQL, Python, dbt/Airflow or similar, cloud data warehouses).
Solid data science foundation — statistics, ML, experiment design, and the judgment to know when a simple model beats a complex one.
Working knowledge of people/HR data and the sensitivity, ethics, and nuance it demands.
Hands-on experience with LLMs and agentic frameworks — building automations, prompts, tool-use, and evaluation loops.
Strong systems thinking: you see how components connect and design for the whole, not just the part in front of you.
Excellent communication — you can explain a model to an executive and a workflow to an engineer

Nice To Haves

Experience with people analytics platforms (Workday, Visier, etc.).
Background in organizational network analysis or workforce planning.
Experience deploying AI in regulated or privacy-sensitive environments.

Responsibilities

Design, build, and maintain reliable data pipelines that unify people data across HRIS, ATS, performance, compensation, and engagement systems.
Model data for analytics and ML use, with a focus on quality, lineage, privacy, and governance of sensitive workforce data.
Build predictive and diagnostic models (attrition, hiring funnel health, org network analysis, compensation equity, workforce planning).
Translate ambiguous people questions into rigorous, defensible analyses — and translate results back into decisions leaders can act on.
Partner on our semi-annual employee engagement survey — from instrument design and data collection to analysis, driver identification, and turning results into actionable insight for leaders.
Design and deploy AI agents and automations that operationalize insight: monitoring signals, generating reports, drafting recommendations, and triggering workflows without manual effort.
Establish the guardrails, evaluation, and human-in-the-loop patterns that make agentic systems safe and trustworthy on sensitive data.
Own the architecture that ties pipelines, models, and agents into one coherent system — and continuously evolve it as tools and needs change.
Set the technical direction and standards for People data and AI, and raise the bar through code review, design docs, and mentorship of peers (leading by influence, not by managing a team).
Partner with People, Data Platform, Security, and Legal to ensure the system is compliant, scalable, and genuinely useful.