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HR Data Quality & AI Readiness Project Manager

GE Vernova
Remote, United States, United StatesRemotefull_timeVerifiedPosted 15 Jun 2026
💰 $203,900/yr($122,400/yr$203,900/yr)

About the role

Job Description Summary

About the Opportunity

At GE Vernova, we are accelerating the energy transition by helping the world electrify and decarbonize. As our business evolves, we are reimagining how HR works — building the data foundation that lets us run on insight, automation, and AI at scale.

We are seeking an HR Data Quality & AI Readiness Project Manager to lead the work that makes that foundation real. AI is only as good as the data beneath it. Before HR can move fast with agents and advanced analytics, our HR data has to be reliable, well understood, and structured for the decisions and tools that depend on it. This role owns that work.

This is hands-on, foundational work. The person in this role partners with every HR Center of Expertise (COE) to find and fix the data quality issues that block trusted reporting and AI readiness, and connects the dots between how data is configured and how it is used downstream. It is the right role for someone who is energized by getting data right — not by writing policy about it.

Job Description

Role Summary 

The HR Data Quality & AI Readiness Project Manager drives HR data quality across the function and prepares the data foundation that AI and agentic solutions will run on. The role partners with each COE to improve the quality of the HR data and processes they own, and bridges the gap between business process configuration decisions and the reporting and AI outcomes those decisions drive. 

Roughly 80% of this role is data quality foundation work. The remaining portion is AI readiness: defining the data dependencies of planned agents and analytics and partnering to confirm the foundation is reliable enough to build on. As the foundation matures, the balance is expected to shift further toward AI readiness. 

This role works in close partnership with HCM Data Governance, Global Solutions, Workday security, and the HR Digital Technology team.  

Key Responsibilities 

Data Quality Foundation (primary focus) 

  • Partner with each HR COE to identify, prioritize, and resolve the data quality issues that undermine trusted reporting and block AI readiness. 

  • Own the connection between business process configuration and reporting outcomes — ensuring that how data is captured in Workday produces the right reporting and analytics result. 

  • Work with the team that configures Workday business processes, exceptions, and rules to define and protect the standards that keep HR data clean at the point of entry. 

  • Establish clear, documented definitions and entry standards for HR data fields, so that practitioners know what to enter, how, and why — reducing avoidable error at the source. 

  • Surface ambiguous or redundant data structures (for example, multiple fields serving similar purposes) and drive decisions that simplify and standardize how HR data is defined and used. 

  • Anticipate emerging data needs as the business evolves and partner to design the right structures to support them. 

  • Validate downstream HR data feeds to confirm the right fields, for the right purpose, reach the right audience. 

AI & Agentic Readiness (secondary focus) 

  • Define the data dependencies of planned HR agents and analytics, in partnership with the agentic roadmap, so readiness is measured against what each solution actually needs.

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Company

GE Vernova

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