Senior Business Intelligence and Governance Architect

Company:

The Boeing Companys Talent Analytics and Innovations team is currently seeking a Senior Business Intelligence and Governance Architect to join our team in Seattle WA; Arlington VA; North Charleston SC or Berkeley MO.

The HR Data Steward ensures the quality integrity privacy and usable governance of HR data and metric definitions across the employee lifecycle and supports responsible use of Artificial Intelligence (AI) / Machine Learning (ML) in Human Resources (HR). This role partners with HR Business Partners HR Information Technology (IT) Finance Data Science/ML Engineering Analytics Legal/Privacy and business leaders to define standards remediate data issues and review models so HR data and AI outputs are accurate fair explainable and compliant.

Position Responsibilities:

• Define document and enforce HR data governance policies data definitions metadata and lineage

• Maintain a data dictionary and feature catalog for HR domains including metric definitions and 3rd party datasets

• Act as subject-matter expert for HR data elements (hire-to-retire) data flows and master records

• Monitor measure and improve data quality (completeness accuracy consistency timeliness uniqueness); investigate root causes and coordinate remediation

• Implement data-validation rules data-quality dashboards Key Performance Indicators (KPI) and Service Level Agreement tracking

• Manage exception and reconciliation processes with HR operations Talent Acquisition Development and HR IT teams

• Support reporting and analytics by providing data context certified datasets and guidance on usage

• Ensure HR data handling adheres to privacy security and retention policies (e.g. GDPR CCPA); coordinate with Legal Privacy and Security teams

• Deliver user training and change management on data-management and usage best practices and governance processes

• Participate in AI/ML model governance lifecycle: intake review approval monitoring and decommissioning for HR models

• Review datasets used for training/validation: confirm representativeness label quality feature provenance and linkage to canonical HR records

• Evaluate model inputs and outputs for appropriateness interpretability and the absence of impermissible/sensitive attributes unless explicitly justified and approved

• Define and apply evaluation criteria and metrics relevant to HR (accuracy calibration precision/recall and fairness measures such as demographic parity or equalized odds) and interpret their operational implications

• Require and review documentation artifacts: model cards data lineage feature catalogs version history evaluation reports and risk assessments

• Ensure explainability human-in-the-loop controls and decision-review processes for models influencing hiring promotion compensation performance management or disciplinary actions

• Monitor post-deployment performance and drift; trigger alerts remediation or retraining when thresholds are exceeded

• Enforce data minimization and privacy-preserving techniques (de-identification synthetic data access controls) for model training and inference

• Maintain or review audit trails for model predictions and decision logs to support investigations and compliance requests

• Coordinate model risk reviews and approvals with Ethics/AI governance Legal/Privacy Security and HR leadership

• Educate HR stakeholders on model capabilities limitations appropriate use and reporting obligations

This position is expected to be 100% onsite. The selected candidate will be required to work onsite at one of the listed location options.

BasicQualifications (Required Skills/Experience):

• 10 years of experience in human resources operations human resources information systems human resources analytics or data governance

• 10 years of experience in Business Intelligence/data analytics tools (Microsoft Power BI Dashboards SQL Tableau etc.)

• 5 years of experience with SQL and Graph databases

• 5 years of experience with privacy-preserving techniques (de-identification synthetic data access controls)

Preferred Qualifications (Desired Skills/Experience):

• Bachelors degree in Human Resources Information Management Data Science Business or related field (or equivalent experience)

• Experience interpreting model and fairness metrics and translate technical findings into business risk and mitigation actions

• Experience with AI/ML model governance or model review responsibilities

• Experience with ML lifecycle concepts model registries and explainability/fairness tools (examples: MLflow model registries SHAP LIME AIF360)

• Strong analytical problem-solving and documentation skills

Conflict of Interest:
Successful candidates for this job must satisfy the Companys Conflict of Interest (COI) assessment process.

Drug Free Workplace:

Boeing is a Drug Free Workplace where post offer applicants and employees are subject to testing for marijuana cocaine opioids amphetamines PCP and alcohol when criteria is met as outlined in our policies.

Pay & Benefits:

At Boeing we strive to deliver a Total Rewards package that will attract engage and retain the top talent. Elements of the Total Rewards package include competitive base pay and variable compensation opportunities.

The Boeing Company also provides eligible employees with an opportunity to enroll in a variety of benefit programs generally including health insurance flexible spending accounts health savings accounts retirement savings plans life and disability insurance programs and a number of programs that provide for both paid and unpaid time away from work.

The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location date of hire and the applicability of collective bargaining agreements.

Pay is based upon candidate experience and qualifications as well as market and business considerations.

Summary pay range: $149600 $216200

Language Requirements:

Education:

Relocation:

Export Control Requirement:

Safety Sensitive:

Security Clearance:

Visa Sponsorship:

Contingent Upon Award Program

Shift:

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